Last updated: 2020-11-19
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Knit directory: pools-projects/
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Rmd | 34e8a9d | noah-padgett | 2020-11-19 | updated pilot FAs |
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Prior to conducting the EFA, we expect that the four factors will emerge from a four-factor solution.
source("code/load_packages.R")
mydata <- read.table("data/data-2020-11-16/pools_data_split1_2020_11_16.txt", sep="\t", header=T)
dat <- mydata[,7:63]
cov.dat <- cov(dat)
For the basic item analysis, we conducted these by the a priori item groups to get a sense of how the initially proposed items fit together.
# item analysis
fit <- psychometric::item.exam(dat[, paste0("Q4_",1:19)])
kable(fit[,c(1:4,7:8)], format="html", digits=3) %>%
kable_styling(full_width = T)%>%
scroll_box(width="100%")
Sample.SD | Item.total | Item.Tot.woi | Difficulty | Item.Reliab | Item.Rel.woi | |
---|---|---|---|---|---|---|
Q4_1 | 0.866 | 0.750 | 0.717 | 2.460 | 0.649 | 0.621 |
Q4_2 | 0.819 | 0.789 | 0.763 | 2.305 | 0.646 | 0.624 |
Q4_3 | 0.834 | 0.744 | 0.712 | 2.537 | 0.620 | 0.593 |
Q4_4 | 0.816 | 0.772 | 0.743 | 2.640 | 0.629 | 0.605 |
Q4_5 | 0.880 | 0.731 | 0.696 | 2.320 | 0.643 | 0.612 |
Q4_6 | 0.981 | 0.650 | 0.601 | 2.872 | 0.637 | 0.589 |
Q4_7 | 0.938 | 0.515 | 0.457 | 3.582 | 0.483 | 0.428 |
Q4_8 | 0.927 | 0.777 | 0.745 | 2.287 | 0.719 | 0.690 |
Q4_9 | 1.007 | 0.701 | 0.657 | 2.463 | 0.705 | 0.660 |
Q4_10 | 0.789 | 0.730 | 0.698 | 2.582 | 0.575 | 0.550 |
Q4_11 | 0.955 | 0.792 | 0.761 | 2.500 | 0.755 | 0.725 |
Q4_12 | 1.051 | 0.696 | 0.649 | 2.195 | 0.730 | 0.681 |
Q4_13 | 0.876 | 0.650 | 0.607 | 1.595 | 0.569 | 0.531 |
Q4_14 | 0.895 | 0.716 | 0.679 | 2.659 | 0.640 | 0.607 |
Q4_15 | 0.917 | 0.789 | 0.759 | 2.375 | 0.722 | 0.695 |
Q4_16 | 0.941 | 0.726 | 0.688 | 2.457 | 0.682 | 0.646 |
Q4_17 | 0.964 | 0.720 | 0.680 | 2.198 | 0.694 | 0.655 |
Q4_18 | 0.823 | 0.843 | 0.822 | 2.360 | 0.693 | 0.676 |
Q4_19 | 0.970 | 0.793 | 0.762 | 2.543 | 0.768 | 0.738 |
# preliminary reliability
psych::alpha(dat[, paste0("Q4_",1:19)])
Reliability analysis
Call: psych::alpha(x = dat[, paste0("Q4_", 1:19)])
raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
0.95 0.95 0.96 0.51 20 0.004 2.5 0.66 0.51
lower alpha upper 95% confidence boundaries
0.94 0.95 0.96
Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
Q4_1 0.95 0.95 0.96 0.51 18 0.0042 0.0103 0.51
Q4_2 0.95 0.95 0.96 0.50 18 0.0043 0.0103 0.51
Q4_3 0.95 0.95 0.96 0.51 18 0.0042 0.0101 0.51
Q4_4 0.95 0.95 0.96 0.50 18 0.0042 0.0105 0.51
Q4_5 0.95 0.95 0.96 0.51 19 0.0042 0.0109 0.51
Q4_6 0.95 0.95 0.96 0.52 19 0.0041 0.0105 0.53
Q4_7 0.95 0.95 0.96 0.53 20 0.0039 0.0069 0.53
Q4_8 0.95 0.95 0.96 0.50 18 0.0043 0.0106 0.51
Q4_9 0.95 0.95 0.96 0.51 19 0.0041 0.0104 0.52
Q4_10 0.95 0.95 0.96 0.51 19 0.0042 0.0108 0.51
Q4_11 0.95 0.95 0.96 0.50 18 0.0043 0.0108 0.51
Q4_12 0.95 0.95 0.96 0.51 19 0.0041 0.0105 0.52
Q4_13 0.95 0.95 0.96 0.52 19 0.0041 0.0094 0.52
Q4_14 0.95 0.95 0.96 0.51 19 0.0042 0.0109 0.52
Q4_15 0.95 0.95 0.96 0.50 18 0.0043 0.0103 0.51
Q4_16 0.95 0.95 0.96 0.51 19 0.0042 0.0107 0.52
Q4_17 0.95 0.95 0.96 0.51 19 0.0042 0.0108 0.52
Q4_18 0.95 0.95 0.96 0.50 18 0.0043 0.0096 0.50
Q4_19 0.95 0.95 0.96 0.50 18 0.0043 0.0105 0.51
Item statistics
n raw.r std.r r.cor r.drop mean sd
Q4_1 328 0.75 0.76 0.74 0.72 2.5 0.87
Q4_2 328 0.79 0.80 0.79 0.76 2.3 0.82
Q4_3 328 0.74 0.75 0.74 0.71 2.5 0.83
Q4_4 328 0.77 0.78 0.77 0.74 2.6 0.82
Q4_5 328 0.73 0.73 0.72 0.70 2.3 0.88
Q4_6 328 0.65 0.65 0.62 0.60 2.9 0.98
Q4_7 328 0.52 0.51 0.48 0.46 3.6 0.94
Q4_8 328 0.78 0.78 0.76 0.75 2.3 0.93
Q4_9 328 0.70 0.70 0.68 0.66 2.5 1.01
Q4_10 328 0.73 0.74 0.72 0.70 2.6 0.79
Q4_11 328 0.79 0.79 0.78 0.76 2.5 0.95
Q4_12 328 0.70 0.69 0.67 0.65 2.2 1.05
Q4_13 328 0.65 0.65 0.63 0.61 1.6 0.88
Q4_14 328 0.72 0.72 0.70 0.68 2.7 0.89
Q4_15 328 0.79 0.79 0.78 0.76 2.4 0.92
Q4_16 328 0.73 0.72 0.71 0.69 2.5 0.94
Q4_17 328 0.72 0.72 0.70 0.68 2.2 0.96
Q4_18 328 0.84 0.85 0.84 0.82 2.4 0.82
Q4_19 328 0.79 0.79 0.78 0.76 2.5 0.97
Non missing response frequency for each item
1 2 3 4 5 miss
Q4_1 0.13 0.38 0.39 0.09 0.01 0
Q4_2 0.15 0.47 0.32 0.05 0.01 0
Q4_3 0.10 0.37 0.44 0.08 0.02 0
Q4_4 0.09 0.28 0.54 0.08 0.02 0
Q4_5 0.16 0.47 0.28 0.08 0.01 0
Q4_6 0.09 0.23 0.44 0.20 0.05 0
Q4_7 0.04 0.09 0.24 0.52 0.11 0
Q4_8 0.20 0.43 0.28 0.07 0.02 0
Q4_9 0.15 0.42 0.27 0.12 0.04 0
Q4_10 0.09 0.30 0.54 0.04 0.02 0
Q4_11 0.16 0.34 0.38 0.10 0.02 0
Q4_12 0.28 0.40 0.18 0.11 0.03 0
Q4_13 0.59 0.29 0.08 0.02 0.02 0
Q4_14 0.11 0.27 0.50 0.09 0.03 0
Q4_15 0.16 0.41 0.33 0.07 0.02 0
Q4_16 0.17 0.33 0.40 0.08 0.02 0
Q4_17 0.26 0.39 0.25 0.08 0.02 0
Q4_18 0.13 0.47 0.34 0.06 0.01 0
Q4_19 0.14 0.35 0.39 0.08 0.04 0
# item analysis
fit <- psychometric::item.exam(dat[, paste0("Q5_",1:12)])
kable(fit[,c(1:4,7:8)], format="html", digits=3) %>%
kable_styling(full_width = T)%>%
scroll_box(width="100%")
Sample.SD | Item.total | Item.Tot.woi | Difficulty | Item.Reliab | Item.Rel.woi | |
---|---|---|---|---|---|---|
Q5_1 | 0.951 | 0.700 | 0.636 | 2.637 | 0.665 | 0.604 |
Q5_2 | 1.035 | 0.742 | 0.680 | 2.954 | 0.767 | 0.703 |
Q5_3 | 1.046 | 0.770 | 0.713 | 2.662 | 0.804 | 0.744 |
Q5_4 | 1.106 | 0.732 | 0.663 | 3.500 | 0.808 | 0.732 |
Q5_5 | 1.034 | 0.680 | 0.607 | 3.530 | 0.702 | 0.627 |
Q5_6 | 0.906 | 0.809 | 0.768 | 2.927 | 0.732 | 0.694 |
Q5_7 | 0.942 | 0.672 | 0.605 | 2.704 | 0.632 | 0.569 |
Q5_8 | 1.055 | 0.800 | 0.748 | 2.905 | 0.842 | 0.788 |
Q5_9 | 0.995 | 0.779 | 0.726 | 2.610 | 0.774 | 0.722 |
Q5_10 | 0.837 | 0.667 | 0.607 | 2.622 | 0.557 | 0.508 |
Q5_11 | 0.951 | 0.665 | 0.596 | 2.707 | 0.631 | 0.566 |
Q5_12 | 0.952 | 0.708 | 0.646 | 2.881 | 0.673 | 0.614 |
# preliminary reliability
psych::alpha(dat[, paste0("Q5_",1:12)])
Reliability analysis
Call: psych::alpha(x = dat[, paste0("Q5_", 1:12)])
raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
0.92 0.92 0.93 0.49 11 0.0066 2.9 0.72 0.48
lower alpha upper 95% confidence boundaries
0.91 0.92 0.93
Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
Q5_1 0.91 0.91 0.92 0.49 10.6 0.0071 0.0087 0.48
Q5_2 0.91 0.91 0.92 0.48 10.3 0.0073 0.0085 0.48
Q5_3 0.91 0.91 0.92 0.48 10.1 0.0074 0.0081 0.47
Q5_4 0.91 0.91 0.92 0.49 10.4 0.0071 0.0069 0.49
Q5_5 0.91 0.92 0.92 0.49 10.8 0.0070 0.0056 0.49
Q5_6 0.91 0.91 0.92 0.47 9.9 0.0075 0.0078 0.47
Q5_7 0.91 0.91 0.92 0.49 10.7 0.0070 0.0083 0.49
Q5_8 0.91 0.91 0.92 0.48 10.0 0.0075 0.0083 0.47
Q5_9 0.91 0.91 0.92 0.48 10.0 0.0074 0.0084 0.47
Q5_10 0.91 0.91 0.92 0.49 10.7 0.0070 0.0086 0.49
Q5_11 0.91 0.92 0.92 0.50 10.8 0.0070 0.0085 0.49
Q5_12 0.91 0.91 0.92 0.49 10.5 0.0071 0.0094 0.48
Item statistics
n raw.r std.r r.cor r.drop mean sd
Q5_1 328 0.70 0.70 0.67 0.64 2.6 0.95
Q5_2 328 0.74 0.74 0.71 0.68 3.0 1.04
Q5_3 328 0.77 0.77 0.75 0.71 2.7 1.05
Q5_4 328 0.73 0.72 0.71 0.66 3.5 1.11
Q5_5 328 0.68 0.67 0.66 0.61 3.5 1.03
Q5_6 328 0.81 0.81 0.80 0.77 2.9 0.91
Q5_7 328 0.67 0.68 0.64 0.60 2.7 0.94
Q5_8 328 0.80 0.80 0.78 0.75 2.9 1.06
Q5_9 328 0.78 0.78 0.76 0.73 2.6 1.00
Q5_10 328 0.67 0.68 0.64 0.61 2.6 0.84
Q5_11 328 0.66 0.67 0.63 0.60 2.7 0.95
Q5_12 328 0.71 0.71 0.67 0.65 2.9 0.95
Non missing response frequency for each item
1 2 3 4 5 miss
Q5_1 0.12 0.32 0.40 0.14 0.03 0
Q5_2 0.10 0.20 0.38 0.27 0.05 0
Q5_3 0.15 0.29 0.35 0.17 0.04 0
Q5_4 0.08 0.11 0.21 0.46 0.15 0
Q5_5 0.05 0.12 0.21 0.48 0.14 0
Q5_6 0.09 0.15 0.52 0.21 0.02 0
Q5_7 0.13 0.22 0.51 0.11 0.03 0
Q5_8 0.12 0.19 0.39 0.24 0.05 0
Q5_9 0.14 0.32 0.37 0.14 0.03 0
Q5_10 0.13 0.21 0.59 0.06 0.02 0
Q5_11 0.11 0.30 0.41 0.17 0.02 0
Q5_12 0.10 0.17 0.50 0.19 0.04 0
# item analysis
fit <- psychometric::item.exam(dat[, paste0("Q6_",1:11)])
kable(fit[,c(1:4,7:8)], format="html", digits=3) %>%
kable_styling(full_width = T)%>%
scroll_box(width="100%")
Sample.SD | Item.total | Item.Tot.woi | Difficulty | Item.Reliab | Item.Rel.woi | |
---|---|---|---|---|---|---|
Q6_1 | 0.844 | 0.722 | 0.660 | 1.701 | 0.608 | 0.556 |
Q6_2 | 0.912 | 0.780 | 0.725 | 2.079 | 0.711 | 0.660 |
Q6_3 | 0.924 | 0.767 | 0.708 | 1.930 | 0.708 | 0.653 |
Q6_4 | 0.927 | 0.723 | 0.654 | 2.076 | 0.669 | 0.606 |
Q6_5 | 1.033 | 0.590 | 0.487 | 2.351 | 0.608 | 0.502 |
Q6_6 | 0.820 | 0.797 | 0.751 | 1.832 | 0.653 | 0.615 |
Q6_7 | 0.875 | 0.832 | 0.790 | 2.162 | 0.727 | 0.690 |
Q6_8 | 0.903 | 0.818 | 0.770 | 2.113 | 0.738 | 0.695 |
Q6_9 | 1.222 | 0.581 | 0.455 | 2.768 | 0.709 | 0.556 |
Q6_10 | 0.913 | 0.625 | 0.541 | 2.887 | 0.570 | 0.493 |
Q6_11 | 0.970 | 0.706 | 0.630 | 2.814 | 0.684 | 0.610 |
# preliminary reliability
psych::alpha(dat[, paste0("Q6_",1:11)])
Reliability analysis
Call: psych::alpha(x = dat[, paste0("Q6_", 1:11)])
raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
0.9 0.91 0.92 0.47 9.9 0.0082 2.2 0.67 0.44
lower alpha upper 95% confidence boundaries
0.89 0.9 0.92
Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
Q6_1 0.89 0.90 0.91 0.47 9.0 0.0091 0.022 0.43
Q6_2 0.89 0.90 0.91 0.46 8.6 0.0093 0.020 0.43
Q6_3 0.89 0.90 0.91 0.46 8.7 0.0093 0.020 0.43
Q6_4 0.89 0.90 0.91 0.47 9.0 0.0090 0.020 0.43
Q6_5 0.90 0.91 0.92 0.50 10.0 0.0082 0.023 0.56
Q6_6 0.89 0.89 0.91 0.46 8.5 0.0094 0.023 0.42
Q6_7 0.89 0.89 0.91 0.45 8.3 0.0097 0.023 0.42
Q6_8 0.89 0.89 0.91 0.46 8.4 0.0096 0.023 0.42
Q6_9 0.91 0.91 0.92 0.51 10.2 0.0077 0.020 0.56
Q6_10 0.90 0.91 0.92 0.49 9.7 0.0086 0.024 0.53
Q6_11 0.89 0.90 0.91 0.48 9.2 0.0090 0.026 0.44
Item statistics
n raw.r std.r r.cor r.drop mean sd
Q6_1 328 0.72 0.73 0.71 0.66 1.7 0.84
Q6_2 328 0.78 0.79 0.78 0.72 2.1 0.91
Q6_3 328 0.77 0.78 0.77 0.71 1.9 0.92
Q6_4 328 0.72 0.74 0.72 0.65 2.1 0.93
Q6_5 328 0.59 0.58 0.51 0.49 2.4 1.03
Q6_6 328 0.80 0.81 0.79 0.75 1.8 0.82
Q6_7 328 0.83 0.84 0.83 0.79 2.2 0.88
Q6_8 328 0.82 0.82 0.81 0.77 2.1 0.90
Q6_9 328 0.58 0.55 0.49 0.46 2.8 1.22
Q6_10 328 0.63 0.62 0.57 0.54 2.9 0.91
Q6_11 328 0.71 0.70 0.66 0.63 2.8 0.97
Non missing response frequency for each item
1 2 3 4 5 miss
Q6_1 0.49 0.36 0.09 0.05 0.00 0
Q6_2 0.27 0.47 0.17 0.07 0.01 0
Q6_3 0.36 0.45 0.13 0.05 0.02 0
Q6_4 0.29 0.43 0.20 0.06 0.01 0
Q6_5 0.19 0.46 0.21 0.10 0.04 0
Q6_6 0.37 0.48 0.11 0.03 0.01 0
Q6_7 0.21 0.50 0.20 0.07 0.01 0
Q6_8 0.25 0.47 0.20 0.07 0.01 0
Q6_9 0.16 0.28 0.30 0.14 0.12 0
Q6_10 0.10 0.15 0.57 0.15 0.04 0
Q6_11 0.11 0.21 0.49 0.14 0.05 0
fit <- psychometric::item.exam(dat[, paste0("Q7_",1:15)])
kable(fit[,c(1:4,7:8)], format="html", digits=3) %>%
kable_styling(full_width = T)%>%
scroll_box(width="100%")
Sample.SD | Item.total | Item.Tot.woi | Difficulty | Item.Reliab | Item.Rel.woi | |
---|---|---|---|---|---|---|
Q7_1 | 0.901 | 0.748 | 0.703 | 2.463 | 0.673 | 0.633 |
Q7_2 | 0.857 | 0.738 | 0.694 | 2.692 | 0.631 | 0.594 |
Q7_3 | 1.012 | 0.712 | 0.656 | 3.558 | 0.720 | 0.663 |
Q7_4 | 0.980 | 0.732 | 0.681 | 2.841 | 0.716 | 0.666 |
Q7_5 | 0.948 | 0.808 | 0.770 | 2.875 | 0.765 | 0.729 |
Q7_6 | 0.920 | 0.745 | 0.699 | 2.933 | 0.684 | 0.642 |
Q7_7 | 1.014 | 0.736 | 0.683 | 3.652 | 0.745 | 0.692 |
Q7_8 | 0.877 | 0.731 | 0.685 | 2.814 | 0.640 | 0.600 |
Q7_9 | 0.993 | 0.716 | 0.662 | 2.567 | 0.710 | 0.656 |
Q7_10 | 0.945 | 0.686 | 0.631 | 2.280 | 0.648 | 0.595 |
Q7_11 | 0.840 | 0.745 | 0.704 | 2.744 | 0.625 | 0.590 |
Q7_12 | 1.023 | 0.674 | 0.611 | 3.390 | 0.688 | 0.624 |
Q7_13 | 0.989 | 0.454 | 0.370 | 3.579 | 0.449 | 0.365 |
Q7_14 | 0.986 | 0.605 | 0.535 | 3.610 | 0.595 | 0.527 |
Q7_15 | 0.905 | 0.665 | 0.609 | 2.509 | 0.601 | 0.550 |
# preliminary reliability
psych::alpha(dat[, paste0("Q7_",1:15)])
Reliability analysis
Call: psych::alpha(x = dat[, paste0("Q7_", 1:15)])
raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
0.92 0.93 0.94 0.45 12 0.0062 3 0.66 0.47
lower alpha upper 95% confidence boundaries
0.91 0.92 0.94
Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
Q7_1 0.92 0.92 0.93 0.45 11 0.0067 0.017 0.47
Q7_2 0.92 0.92 0.94 0.45 11 0.0067 0.018 0.47
Q7_3 0.92 0.92 0.93 0.45 12 0.0066 0.017 0.48
Q7_4 0.92 0.92 0.94 0.45 11 0.0067 0.017 0.47
Q7_5 0.92 0.92 0.93 0.44 11 0.0069 0.017 0.46
Q7_6 0.92 0.92 0.94 0.45 11 0.0067 0.018 0.46
Q7_7 0.92 0.92 0.93 0.45 11 0.0067 0.017 0.48
Q7_8 0.92 0.92 0.94 0.45 11 0.0067 0.018 0.47
Q7_9 0.92 0.92 0.94 0.45 12 0.0066 0.017 0.47
Q7_10 0.92 0.92 0.93 0.45 12 0.0065 0.015 0.47
Q7_11 0.92 0.92 0.93 0.45 11 0.0067 0.018 0.47
Q7_12 0.92 0.92 0.94 0.46 12 0.0065 0.019 0.49
Q7_13 0.93 0.93 0.94 0.48 13 0.0059 0.011 0.50
Q7_14 0.92 0.92 0.94 0.47 12 0.0063 0.017 0.49
Q7_15 0.92 0.92 0.94 0.46 12 0.0065 0.016 0.48
Item statistics
n raw.r std.r r.cor r.drop mean sd
Q7_1 328 0.75 0.75 0.74 0.70 2.5 0.90
Q7_2 328 0.74 0.74 0.73 0.69 2.7 0.86
Q7_3 328 0.71 0.71 0.69 0.66 3.6 1.01
Q7_4 328 0.73 0.73 0.71 0.68 2.8 0.98
Q7_5 328 0.81 0.81 0.80 0.77 2.9 0.95
Q7_6 328 0.74 0.75 0.72 0.70 2.9 0.92
Q7_7 328 0.74 0.73 0.72 0.68 3.7 1.01
Q7_8 328 0.73 0.73 0.71 0.69 2.8 0.88
Q7_9 328 0.72 0.72 0.70 0.66 2.6 0.99
Q7_10 328 0.69 0.69 0.68 0.63 2.3 0.95
Q7_11 328 0.75 0.75 0.74 0.70 2.7 0.84
Q7_12 328 0.67 0.67 0.64 0.61 3.4 1.02
Q7_13 328 0.45 0.45 0.39 0.37 3.6 0.99
Q7_14 328 0.60 0.60 0.56 0.54 3.6 0.99
Q7_15 328 0.66 0.67 0.65 0.61 2.5 0.91
Non missing response frequency for each item
1 2 3 4 5 miss
Q7_1 0.15 0.35 0.40 0.09 0.01 0
Q7_2 0.11 0.21 0.57 0.09 0.02 0
Q7_3 0.05 0.10 0.22 0.50 0.13 0
Q7_4 0.10 0.21 0.47 0.17 0.05 0
Q7_5 0.10 0.18 0.51 0.17 0.04 0
Q7_6 0.08 0.17 0.53 0.18 0.04 0
Q7_7 0.05 0.09 0.17 0.53 0.16 0
Q7_8 0.10 0.17 0.55 0.15 0.02 0
Q7_9 0.16 0.29 0.41 0.12 0.03 0
Q7_10 0.20 0.45 0.25 0.08 0.02 0
Q7_11 0.10 0.19 0.59 0.11 0.02 0
Q7_12 0.07 0.09 0.32 0.43 0.10 0
Q7_13 0.02 0.11 0.32 0.36 0.19 0
Q7_14 0.05 0.08 0.24 0.48 0.15 0
Q7_15 0.14 0.33 0.43 0.08 0.02 0
First, we investigated the raw correlations among the variables.
# Pearson correlation matrix
corr.ppm <- cor(dat)
kable(corr.ppm,digits=3,format = "html")%>%
kable_styling(full_width = T)%>%
scroll_box(width="100%", height="500px")
Q4_1 | Q4_2 | Q4_3 | Q4_4 | Q4_5 | Q4_6 | Q4_7 | Q4_8 | Q4_9 | Q4_10 | Q4_11 | Q4_12 | Q4_13 | Q4_14 | Q4_15 | Q4_16 | Q4_17 | Q4_18 | Q4_19 | Q5_1 | Q5_2 | Q5_3 | Q5_4 | Q5_5 | Q5_6 | Q5_7 | Q5_8 | Q5_9 | Q5_10 | Q5_11 | Q5_12 | Q6_1 | Q6_2 | Q6_3 | Q6_4 | Q6_5 | Q6_6 | Q6_7 | Q6_8 | Q6_9 | Q6_10 | Q6_11 | Q7_1 | Q7_2 | Q7_3 | Q7_4 | Q7_5 | Q7_6 | Q7_7 | Q7_8 | Q7_9 | Q7_10 | Q7_11 | Q7_12 | Q7_13 | Q7_14 | Q7_15 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Q4_1 | 1.000 | 0.629 | 0.685 | 0.672 | 0.508 | 0.473 | 0.316 | 0.585 | 0.431 | 0.568 | 0.586 | 0.408 | 0.408 | 0.543 | 0.533 | 0.540 | 0.469 | 0.655 | 0.495 | 0.422 | 0.337 | 0.362 | 0.349 | 0.283 | 0.394 | 0.298 | 0.319 | 0.432 | 0.350 | 0.424 | 0.330 | 0.293 | 0.275 | 0.235 | 0.257 | 0.250 | 0.290 | 0.369 | 0.312 | 0.245 | 0.309 | 0.357 | 0.458 | 0.340 | 0.247 | 0.331 | 0.398 | 0.357 | 0.287 | 0.298 | 0.527 | 0.495 | 0.423 | 0.307 | 0.127 | 0.218 | 0.445 |
Q4_2 | 0.629 | 1.000 | 0.646 | 0.636 | 0.657 | 0.486 | 0.341 | 0.621 | 0.514 | 0.552 | 0.563 | 0.488 | 0.518 | 0.485 | 0.592 | 0.501 | 0.523 | 0.730 | 0.561 | 0.464 | 0.381 | 0.414 | 0.334 | 0.292 | 0.413 | 0.307 | 0.369 | 0.446 | 0.378 | 0.472 | 0.368 | 0.265 | 0.315 | 0.271 | 0.243 | 0.340 | 0.390 | 0.392 | 0.300 | 0.266 | 0.365 | 0.422 | 0.483 | 0.387 | 0.285 | 0.342 | 0.474 | 0.384 | 0.352 | 0.394 | 0.471 | 0.505 | 0.407 | 0.281 | 0.129 | 0.197 | 0.454 |
Q4_3 | 0.685 | 0.646 | 1.000 | 0.680 | 0.490 | 0.413 | 0.326 | 0.607 | 0.508 | 0.597 | 0.572 | 0.351 | 0.370 | 0.459 | 0.540 | 0.512 | 0.476 | 0.622 | 0.577 | 0.431 | 0.347 | 0.356 | 0.331 | 0.293 | 0.429 | 0.308 | 0.350 | 0.448 | 0.335 | 0.480 | 0.292 | 0.302 | 0.270 | 0.247 | 0.244 | 0.296 | 0.302 | 0.367 | 0.309 | 0.245 | 0.284 | 0.369 | 0.449 | 0.356 | 0.289 | 0.303 | 0.406 | 0.390 | 0.377 | 0.337 | 0.488 | 0.479 | 0.472 | 0.345 | 0.148 | 0.211 | 0.411 |
Q4_4 | 0.672 | 0.636 | 0.680 | 1.000 | 0.519 | 0.489 | 0.430 | 0.610 | 0.498 | 0.645 | 0.573 | 0.439 | 0.381 | 0.489 | 0.524 | 0.526 | 0.507 | 0.663 | 0.530 | 0.419 | 0.368 | 0.348 | 0.383 | 0.365 | 0.473 | 0.406 | 0.387 | 0.429 | 0.409 | 0.384 | 0.437 | 0.234 | 0.306 | 0.299 | 0.226 | 0.281 | 0.408 | 0.394 | 0.354 | 0.290 | 0.364 | 0.460 | 0.469 | 0.476 | 0.370 | 0.487 | 0.499 | 0.473 | 0.403 | 0.436 | 0.521 | 0.516 | 0.517 | 0.334 | 0.134 | 0.308 | 0.477 |
Q4_5 | 0.508 | 0.657 | 0.490 | 0.519 | 1.000 | 0.522 | 0.318 | 0.532 | 0.429 | 0.501 | 0.540 | 0.504 | 0.526 | 0.462 | 0.552 | 0.454 | 0.505 | 0.617 | 0.545 | 0.450 | 0.392 | 0.440 | 0.353 | 0.270 | 0.386 | 0.373 | 0.411 | 0.534 | 0.389 | 0.499 | 0.407 | 0.327 | 0.368 | 0.366 | 0.277 | 0.270 | 0.456 | 0.425 | 0.389 | 0.288 | 0.368 | 0.460 | 0.510 | 0.387 | 0.279 | 0.368 | 0.418 | 0.367 | 0.368 | 0.370 | 0.491 | 0.550 | 0.347 | 0.282 | 0.085 | 0.173 | 0.474 |
Q4_6 | 0.473 | 0.486 | 0.413 | 0.489 | 0.522 | 1.000 | 0.570 | 0.420 | 0.336 | 0.468 | 0.451 | 0.389 | 0.317 | 0.407 | 0.451 | 0.461 | 0.395 | 0.497 | 0.446 | 0.373 | 0.479 | 0.441 | 0.395 | 0.326 | 0.458 | 0.379 | 0.440 | 0.494 | 0.347 | 0.415 | 0.426 | 0.316 | 0.435 | 0.364 | 0.300 | 0.280 | 0.350 | 0.363 | 0.324 | 0.276 | 0.387 | 0.486 | 0.496 | 0.415 | 0.380 | 0.418 | 0.400 | 0.394 | 0.370 | 0.328 | 0.448 | 0.497 | 0.376 | 0.300 | 0.225 | 0.400 | 0.466 |
Q4_7 | 0.316 | 0.341 | 0.326 | 0.430 | 0.318 | 0.570 | 1.000 | 0.310 | 0.270 | 0.412 | 0.415 | 0.300 | 0.150 | 0.351 | 0.286 | 0.352 | 0.284 | 0.318 | 0.368 | 0.337 | 0.399 | 0.311 | 0.411 | 0.317 | 0.342 | 0.368 | 0.414 | 0.355 | 0.344 | 0.335 | 0.396 | 0.205 | 0.271 | 0.231 | 0.255 | 0.161 | 0.294 | 0.295 | 0.287 | 0.238 | 0.337 | 0.429 | 0.342 | 0.414 | 0.452 | 0.400 | 0.409 | 0.357 | 0.425 | 0.340 | 0.334 | 0.312 | 0.322 | 0.266 | 0.199 | 0.336 | 0.284 |
Q4_8 | 0.585 | 0.621 | 0.607 | 0.610 | 0.532 | 0.420 | 0.310 | 1.000 | 0.594 | 0.574 | 0.574 | 0.498 | 0.486 | 0.513 | 0.586 | 0.470 | 0.559 | 0.642 | 0.619 | 0.417 | 0.352 | 0.400 | 0.271 | 0.217 | 0.360 | 0.307 | 0.375 | 0.433 | 0.325 | 0.404 | 0.354 | 0.286 | 0.320 | 0.352 | 0.302 | 0.291 | 0.409 | 0.489 | 0.407 | 0.310 | 0.352 | 0.406 | 0.415 | 0.369 | 0.253 | 0.296 | 0.371 | 0.363 | 0.269 | 0.359 | 0.434 | 0.487 | 0.397 | 0.246 | 0.082 | 0.156 | 0.398 |
Q4_9 | 0.431 | 0.514 | 0.508 | 0.498 | 0.429 | 0.336 | 0.270 | 0.594 | 1.000 | 0.467 | 0.541 | 0.466 | 0.456 | 0.451 | 0.537 | 0.421 | 0.488 | 0.547 | 0.706 | 0.387 | 0.346 | 0.370 | 0.236 | 0.242 | 0.366 | 0.283 | 0.321 | 0.330 | 0.263 | 0.401 | 0.399 | 0.250 | 0.300 | 0.245 | 0.280 | 0.249 | 0.332 | 0.411 | 0.332 | 0.331 | 0.280 | 0.308 | 0.379 | 0.382 | 0.301 | 0.326 | 0.413 | 0.450 | 0.347 | 0.375 | 0.409 | 0.457 | 0.463 | 0.320 | 0.129 | 0.198 | 0.341 |
Q4_10 | 0.568 | 0.552 | 0.597 | 0.645 | 0.501 | 0.468 | 0.412 | 0.574 | 0.467 | 1.000 | 0.570 | 0.423 | 0.342 | 0.443 | 0.530 | 0.493 | 0.471 | 0.618 | 0.553 | 0.441 | 0.298 | 0.299 | 0.331 | 0.332 | 0.381 | 0.388 | 0.367 | 0.469 | 0.380 | 0.399 | 0.373 | 0.257 | 0.288 | 0.333 | 0.265 | 0.248 | 0.383 | 0.434 | 0.336 | 0.311 | 0.286 | 0.441 | 0.419 | 0.497 | 0.377 | 0.393 | 0.486 | 0.391 | 0.395 | 0.409 | 0.385 | 0.432 | 0.484 | 0.309 | 0.158 | 0.316 | 0.440 |
Q4_11 | 0.586 | 0.563 | 0.572 | 0.573 | 0.540 | 0.451 | 0.415 | 0.574 | 0.541 | 0.570 | 1.000 | 0.558 | 0.473 | 0.544 | 0.592 | 0.558 | 0.530 | 0.650 | 0.677 | 0.470 | 0.401 | 0.406 | 0.316 | 0.266 | 0.428 | 0.440 | 0.414 | 0.528 | 0.486 | 0.458 | 0.395 | 0.323 | 0.344 | 0.324 | 0.323 | 0.355 | 0.428 | 0.448 | 0.442 | 0.383 | 0.374 | 0.451 | 0.526 | 0.447 | 0.334 | 0.392 | 0.542 | 0.453 | 0.347 | 0.414 | 0.435 | 0.481 | 0.469 | 0.385 | 0.204 | 0.292 | 0.508 |
Q4_12 | 0.408 | 0.488 | 0.351 | 0.439 | 0.504 | 0.389 | 0.300 | 0.498 | 0.466 | 0.423 | 0.558 | 1.000 | 0.694 | 0.523 | 0.504 | 0.420 | 0.499 | 0.551 | 0.541 | 0.395 | 0.379 | 0.430 | 0.237 | 0.172 | 0.314 | 0.423 | 0.361 | 0.421 | 0.379 | 0.360 | 0.350 | 0.428 | 0.437 | 0.423 | 0.358 | 0.342 | 0.499 | 0.527 | 0.514 | 0.402 | 0.335 | 0.476 | 0.450 | 0.440 | 0.303 | 0.357 | 0.451 | 0.428 | 0.310 | 0.368 | 0.397 | 0.397 | 0.275 | 0.259 | 0.103 | 0.180 | 0.371 |
Q4_13 | 0.408 | 0.518 | 0.370 | 0.381 | 0.526 | 0.317 | 0.150 | 0.486 | 0.456 | 0.342 | 0.473 | 0.694 | 1.000 | 0.478 | 0.491 | 0.367 | 0.454 | 0.580 | 0.501 | 0.399 | 0.337 | 0.404 | 0.194 | 0.147 | 0.278 | 0.384 | 0.273 | 0.397 | 0.353 | 0.367 | 0.334 | 0.440 | 0.408 | 0.388 | 0.336 | 0.347 | 0.476 | 0.445 | 0.425 | 0.329 | 0.256 | 0.357 | 0.413 | 0.371 | 0.170 | 0.224 | 0.281 | 0.357 | 0.202 | 0.284 | 0.388 | 0.455 | 0.257 | 0.266 | 0.074 | 0.096 | 0.315 |
Q4_14 | 0.543 | 0.485 | 0.459 | 0.489 | 0.462 | 0.407 | 0.351 | 0.513 | 0.451 | 0.443 | 0.544 | 0.523 | 0.478 | 1.000 | 0.671 | 0.586 | 0.444 | 0.566 | 0.521 | 0.465 | 0.429 | 0.461 | 0.309 | 0.259 | 0.460 | 0.399 | 0.374 | 0.502 | 0.358 | 0.457 | 0.419 | 0.403 | 0.359 | 0.344 | 0.349 | 0.335 | 0.422 | 0.481 | 0.438 | 0.442 | 0.428 | 0.529 | 0.478 | 0.437 | 0.336 | 0.332 | 0.462 | 0.463 | 0.371 | 0.398 | 0.490 | 0.421 | 0.380 | 0.360 | 0.217 | 0.271 | 0.427 |
Q4_15 | 0.533 | 0.592 | 0.540 | 0.524 | 0.552 | 0.451 | 0.286 | 0.586 | 0.537 | 0.530 | 0.592 | 0.504 | 0.491 | 0.671 | 1.000 | 0.701 | 0.607 | 0.655 | 0.593 | 0.472 | 0.405 | 0.455 | 0.348 | 0.283 | 0.486 | 0.444 | 0.426 | 0.529 | 0.440 | 0.466 | 0.454 | 0.355 | 0.348 | 0.338 | 0.333 | 0.310 | 0.430 | 0.481 | 0.444 | 0.381 | 0.390 | 0.450 | 0.503 | 0.455 | 0.265 | 0.332 | 0.473 | 0.451 | 0.331 | 0.429 | 0.448 | 0.492 | 0.487 | 0.326 | 0.137 | 0.200 | 0.447 |
Q4_16 | 0.540 | 0.501 | 0.512 | 0.526 | 0.454 | 0.461 | 0.352 | 0.470 | 0.421 | 0.493 | 0.558 | 0.420 | 0.367 | 0.586 | 0.701 | 1.000 | 0.598 | 0.573 | 0.532 | 0.412 | 0.405 | 0.466 | 0.350 | 0.325 | 0.488 | 0.415 | 0.398 | 0.495 | 0.403 | 0.444 | 0.426 | 0.404 | 0.421 | 0.364 | 0.356 | 0.203 | 0.377 | 0.441 | 0.382 | 0.276 | 0.359 | 0.388 | 0.467 | 0.373 | 0.235 | 0.291 | 0.383 | 0.386 | 0.260 | 0.329 | 0.432 | 0.440 | 0.385 | 0.256 | 0.102 | 0.163 | 0.422 |
Q4_17 | 0.469 | 0.523 | 0.476 | 0.507 | 0.505 | 0.395 | 0.284 | 0.559 | 0.488 | 0.471 | 0.530 | 0.499 | 0.454 | 0.444 | 0.607 | 0.598 | 1.000 | 0.615 | 0.535 | 0.382 | 0.328 | 0.373 | 0.234 | 0.164 | 0.367 | 0.364 | 0.310 | 0.348 | 0.400 | 0.400 | 0.336 | 0.321 | 0.309 | 0.352 | 0.305 | 0.274 | 0.421 | 0.455 | 0.413 | 0.296 | 0.380 | 0.360 | 0.376 | 0.341 | 0.281 | 0.360 | 0.432 | 0.367 | 0.333 | 0.394 | 0.432 | 0.452 | 0.403 | 0.272 | 0.097 | 0.149 | 0.399 |
Q4_18 | 0.655 | 0.730 | 0.622 | 0.663 | 0.617 | 0.497 | 0.318 | 0.642 | 0.547 | 0.618 | 0.650 | 0.551 | 0.580 | 0.566 | 0.655 | 0.573 | 0.615 | 1.000 | 0.659 | 0.480 | 0.425 | 0.419 | 0.319 | 0.318 | 0.515 | 0.394 | 0.434 | 0.530 | 0.500 | 0.451 | 0.426 | 0.296 | 0.308 | 0.323 | 0.277 | 0.326 | 0.389 | 0.484 | 0.394 | 0.332 | 0.367 | 0.471 | 0.496 | 0.448 | 0.305 | 0.386 | 0.446 | 0.412 | 0.352 | 0.415 | 0.479 | 0.550 | 0.470 | 0.272 | 0.096 | 0.271 | 0.513 |
Q4_19 | 0.495 | 0.561 | 0.577 | 0.530 | 0.545 | 0.446 | 0.368 | 0.619 | 0.706 | 0.553 | 0.677 | 0.541 | 0.501 | 0.521 | 0.593 | 0.532 | 0.535 | 0.659 | 1.000 | 0.469 | 0.451 | 0.471 | 0.325 | 0.276 | 0.477 | 0.404 | 0.424 | 0.521 | 0.401 | 0.471 | 0.445 | 0.322 | 0.349 | 0.326 | 0.331 | 0.268 | 0.423 | 0.462 | 0.401 | 0.388 | 0.408 | 0.452 | 0.495 | 0.452 | 0.376 | 0.387 | 0.503 | 0.483 | 0.429 | 0.479 | 0.486 | 0.507 | 0.479 | 0.369 | 0.130 | 0.248 | 0.458 |
Q5_1 | 0.422 | 0.464 | 0.431 | 0.419 | 0.450 | 0.373 | 0.337 | 0.417 | 0.387 | 0.441 | 0.470 | 0.395 | 0.399 | 0.465 | 0.472 | 0.412 | 0.382 | 0.480 | 0.469 | 1.000 | 0.511 | 0.574 | 0.391 | 0.330 | 0.494 | 0.388 | 0.462 | 0.551 | 0.465 | 0.508 | 0.466 | 0.303 | 0.277 | 0.242 | 0.208 | 0.298 | 0.349 | 0.379 | 0.304 | 0.362 | 0.301 | 0.417 | 0.536 | 0.426 | 0.309 | 0.329 | 0.468 | 0.399 | 0.363 | 0.384 | 0.490 | 0.423 | 0.462 | 0.382 | 0.156 | 0.256 | 0.435 |
Q5_2 | 0.337 | 0.381 | 0.347 | 0.368 | 0.392 | 0.479 | 0.399 | 0.352 | 0.346 | 0.298 | 0.401 | 0.379 | 0.337 | 0.429 | 0.405 | 0.405 | 0.328 | 0.425 | 0.451 | 0.511 | 1.000 | 0.650 | 0.482 | 0.431 | 0.610 | 0.409 | 0.548 | 0.469 | 0.449 | 0.375 | 0.513 | 0.307 | 0.347 | 0.316 | 0.357 | 0.258 | 0.326 | 0.349 | 0.323 | 0.258 | 0.350 | 0.494 | 0.472 | 0.457 | 0.384 | 0.397 | 0.402 | 0.431 | 0.442 | 0.327 | 0.436 | 0.416 | 0.335 | 0.254 | 0.154 | 0.327 | 0.404 |
Q5_3 | 0.362 | 0.414 | 0.356 | 0.348 | 0.440 | 0.441 | 0.311 | 0.400 | 0.370 | 0.299 | 0.406 | 0.430 | 0.404 | 0.461 | 0.455 | 0.466 | 0.373 | 0.419 | 0.471 | 0.574 | 0.650 | 1.000 | 0.517 | 0.398 | 0.610 | 0.382 | 0.572 | 0.575 | 0.430 | 0.484 | 0.491 | 0.367 | 0.320 | 0.298 | 0.304 | 0.255 | 0.362 | 0.371 | 0.355 | 0.314 | 0.335 | 0.423 | 0.521 | 0.416 | 0.280 | 0.300 | 0.386 | 0.377 | 0.324 | 0.335 | 0.462 | 0.421 | 0.340 | 0.293 | 0.122 | 0.242 | 0.435 |
Q5_4 | 0.349 | 0.334 | 0.331 | 0.383 | 0.353 | 0.395 | 0.411 | 0.271 | 0.236 | 0.331 | 0.316 | 0.237 | 0.194 | 0.309 | 0.348 | 0.350 | 0.234 | 0.319 | 0.325 | 0.391 | 0.482 | 0.517 | 1.000 | 0.781 | 0.586 | 0.371 | 0.539 | 0.433 | 0.396 | 0.355 | 0.440 | 0.200 | 0.246 | 0.253 | 0.198 | 0.210 | 0.268 | 0.210 | 0.191 | 0.174 | 0.298 | 0.386 | 0.414 | 0.421 | 0.439 | 0.308 | 0.363 | 0.346 | 0.469 | 0.314 | 0.345 | 0.322 | 0.356 | 0.308 | 0.145 | 0.370 | 0.310 |
Q5_5 | 0.283 | 0.292 | 0.293 | 0.365 | 0.270 | 0.326 | 0.317 | 0.217 | 0.242 | 0.332 | 0.266 | 0.172 | 0.147 | 0.259 | 0.283 | 0.325 | 0.164 | 0.318 | 0.276 | 0.330 | 0.431 | 0.398 | 0.781 | 1.000 | 0.587 | 0.353 | 0.534 | 0.395 | 0.307 | 0.348 | 0.387 | 0.116 | 0.176 | 0.193 | 0.165 | 0.186 | 0.185 | 0.158 | 0.119 | 0.110 | 0.225 | 0.272 | 0.356 | 0.413 | 0.359 | 0.304 | 0.302 | 0.292 | 0.389 | 0.315 | 0.284 | 0.260 | 0.365 | 0.333 | 0.150 | 0.348 | 0.266 |
Q5_6 | 0.394 | 0.413 | 0.429 | 0.473 | 0.386 | 0.458 | 0.342 | 0.360 | 0.366 | 0.381 | 0.428 | 0.314 | 0.278 | 0.460 | 0.486 | 0.488 | 0.367 | 0.515 | 0.477 | 0.494 | 0.610 | 0.610 | 0.586 | 0.587 | 1.000 | 0.530 | 0.668 | 0.572 | 0.460 | 0.426 | 0.522 | 0.247 | 0.325 | 0.337 | 0.294 | 0.296 | 0.334 | 0.409 | 0.350 | 0.250 | 0.397 | 0.461 | 0.488 | 0.444 | 0.402 | 0.407 | 0.470 | 0.446 | 0.422 | 0.395 | 0.454 | 0.453 | 0.426 | 0.348 | 0.140 | 0.372 | 0.404 |
Q5_7 | 0.298 | 0.307 | 0.308 | 0.406 | 0.373 | 0.379 | 0.368 | 0.307 | 0.283 | 0.388 | 0.440 | 0.423 | 0.384 | 0.399 | 0.444 | 0.415 | 0.364 | 0.394 | 0.404 | 0.388 | 0.409 | 0.382 | 0.371 | 0.353 | 0.530 | 1.000 | 0.538 | 0.571 | 0.525 | 0.412 | 0.445 | 0.346 | 0.437 | 0.436 | 0.344 | 0.317 | 0.442 | 0.511 | 0.460 | 0.405 | 0.356 | 0.492 | 0.464 | 0.497 | 0.340 | 0.360 | 0.431 | 0.415 | 0.311 | 0.429 | 0.369 | 0.372 | 0.403 | 0.298 | 0.135 | 0.211 | 0.331 |
Q5_8 | 0.319 | 0.369 | 0.350 | 0.387 | 0.411 | 0.440 | 0.414 | 0.375 | 0.321 | 0.367 | 0.414 | 0.361 | 0.273 | 0.374 | 0.426 | 0.398 | 0.310 | 0.434 | 0.424 | 0.462 | 0.548 | 0.572 | 0.539 | 0.534 | 0.668 | 0.538 | 1.000 | 0.637 | 0.482 | 0.469 | 0.497 | 0.267 | 0.335 | 0.366 | 0.289 | 0.348 | 0.335 | 0.358 | 0.351 | 0.251 | 0.382 | 0.497 | 0.506 | 0.458 | 0.416 | 0.426 | 0.438 | 0.444 | 0.386 | 0.424 | 0.434 | 0.422 | 0.421 | 0.360 | 0.152 | 0.323 | 0.380 |
Q5_9 | 0.432 | 0.446 | 0.448 | 0.429 | 0.534 | 0.494 | 0.355 | 0.433 | 0.330 | 0.469 | 0.528 | 0.421 | 0.397 | 0.502 | 0.529 | 0.495 | 0.348 | 0.530 | 0.521 | 0.551 | 0.469 | 0.575 | 0.433 | 0.395 | 0.572 | 0.571 | 0.637 | 1.000 | 0.553 | 0.544 | 0.519 | 0.411 | 0.432 | 0.442 | 0.340 | 0.330 | 0.448 | 0.483 | 0.447 | 0.363 | 0.449 | 0.564 | 0.587 | 0.461 | 0.347 | 0.435 | 0.450 | 0.399 | 0.307 | 0.421 | 0.521 | 0.500 | 0.433 | 0.342 | 0.103 | 0.265 | 0.506 |
Q5_10 | 0.350 | 0.378 | 0.335 | 0.409 | 0.389 | 0.347 | 0.344 | 0.325 | 0.263 | 0.380 | 0.486 | 0.379 | 0.353 | 0.358 | 0.440 | 0.403 | 0.400 | 0.500 | 0.401 | 0.465 | 0.449 | 0.430 | 0.396 | 0.307 | 0.460 | 0.525 | 0.482 | 0.553 | 1.000 | 0.425 | 0.435 | 0.264 | 0.280 | 0.333 | 0.301 | 0.221 | 0.420 | 0.384 | 0.388 | 0.261 | 0.364 | 0.429 | 0.436 | 0.426 | 0.289 | 0.363 | 0.422 | 0.396 | 0.335 | 0.416 | 0.398 | 0.417 | 0.414 | 0.298 | 0.040 | 0.280 | 0.344 |
Q5_11 | 0.424 | 0.472 | 0.480 | 0.384 | 0.499 | 0.415 | 0.335 | 0.404 | 0.401 | 0.399 | 0.458 | 0.360 | 0.367 | 0.457 | 0.466 | 0.444 | 0.400 | 0.451 | 0.471 | 0.508 | 0.375 | 0.484 | 0.355 | 0.348 | 0.426 | 0.412 | 0.469 | 0.544 | 0.425 | 1.000 | 0.495 | 0.329 | 0.376 | 0.335 | 0.303 | 0.369 | 0.376 | 0.406 | 0.370 | 0.339 | 0.423 | 0.415 | 0.576 | 0.433 | 0.383 | 0.446 | 0.454 | 0.394 | 0.354 | 0.371 | 0.526 | 0.472 | 0.450 | 0.454 | 0.317 | 0.279 | 0.422 |
Q5_12 | 0.330 | 0.368 | 0.292 | 0.437 | 0.407 | 0.426 | 0.396 | 0.354 | 0.399 | 0.373 | 0.395 | 0.350 | 0.334 | 0.419 | 0.454 | 0.426 | 0.336 | 0.426 | 0.445 | 0.466 | 0.513 | 0.491 | 0.440 | 0.387 | 0.522 | 0.445 | 0.497 | 0.519 | 0.435 | 0.495 | 1.000 | 0.275 | 0.423 | 0.348 | 0.284 | 0.285 | 0.378 | 0.405 | 0.346 | 0.265 | 0.371 | 0.483 | 0.481 | 0.398 | 0.412 | 0.485 | 0.482 | 0.396 | 0.410 | 0.453 | 0.486 | 0.455 | 0.432 | 0.396 | 0.200 | 0.354 | 0.447 |
Q6_1 | 0.293 | 0.265 | 0.302 | 0.234 | 0.327 | 0.316 | 0.205 | 0.286 | 0.250 | 0.257 | 0.323 | 0.428 | 0.440 | 0.403 | 0.355 | 0.404 | 0.321 | 0.296 | 0.322 | 0.303 | 0.307 | 0.367 | 0.200 | 0.116 | 0.247 | 0.346 | 0.267 | 0.411 | 0.264 | 0.329 | 0.275 | 1.000 | 0.695 | 0.652 | 0.573 | 0.286 | 0.577 | 0.559 | 0.566 | 0.280 | 0.286 | 0.369 | 0.472 | 0.300 | 0.117 | 0.220 | 0.278 | 0.289 | 0.143 | 0.185 | 0.378 | 0.389 | 0.237 | 0.256 | 0.124 | 0.080 | 0.364 |
Q6_2 | 0.275 | 0.315 | 0.270 | 0.306 | 0.368 | 0.435 | 0.271 | 0.320 | 0.300 | 0.288 | 0.344 | 0.437 | 0.408 | 0.359 | 0.348 | 0.421 | 0.309 | 0.308 | 0.349 | 0.277 | 0.347 | 0.320 | 0.246 | 0.176 | 0.325 | 0.437 | 0.335 | 0.432 | 0.280 | 0.376 | 0.423 | 0.695 | 1.000 | 0.725 | 0.723 | 0.347 | 0.595 | 0.593 | 0.631 | 0.253 | 0.312 | 0.418 | 0.461 | 0.345 | 0.237 | 0.322 | 0.344 | 0.353 | 0.152 | 0.217 | 0.399 | 0.435 | 0.286 | 0.242 | 0.095 | 0.150 | 0.344 |
Q6_3 | 0.235 | 0.271 | 0.247 | 0.299 | 0.366 | 0.364 | 0.231 | 0.352 | 0.245 | 0.333 | 0.324 | 0.423 | 0.388 | 0.344 | 0.338 | 0.364 | 0.352 | 0.323 | 0.326 | 0.242 | 0.316 | 0.298 | 0.253 | 0.193 | 0.337 | 0.436 | 0.366 | 0.442 | 0.333 | 0.335 | 0.348 | 0.652 | 0.725 | 1.000 | 0.652 | 0.372 | 0.638 | 0.668 | 0.574 | 0.227 | 0.269 | 0.415 | 0.447 | 0.313 | 0.271 | 0.295 | 0.294 | 0.333 | 0.179 | 0.214 | 0.337 | 0.404 | 0.249 | 0.217 | 0.095 | 0.164 | 0.346 |
Q6_4 | 0.257 | 0.243 | 0.244 | 0.226 | 0.277 | 0.300 | 0.255 | 0.302 | 0.280 | 0.265 | 0.323 | 0.358 | 0.336 | 0.349 | 0.333 | 0.356 | 0.305 | 0.277 | 0.331 | 0.208 | 0.357 | 0.304 | 0.198 | 0.165 | 0.294 | 0.344 | 0.289 | 0.340 | 0.301 | 0.303 | 0.284 | 0.573 | 0.723 | 0.652 | 1.000 | 0.250 | 0.560 | 0.592 | 0.640 | 0.191 | 0.299 | 0.366 | 0.357 | 0.315 | 0.189 | 0.320 | 0.265 | 0.329 | 0.142 | 0.217 | 0.328 | 0.394 | 0.304 | 0.162 | 0.022 | 0.096 | 0.278 |
Q6_5 | 0.250 | 0.340 | 0.296 | 0.281 | 0.270 | 0.280 | 0.161 | 0.291 | 0.249 | 0.248 | 0.355 | 0.342 | 0.347 | 0.335 | 0.310 | 0.203 | 0.274 | 0.326 | 0.268 | 0.298 | 0.258 | 0.255 | 0.210 | 0.186 | 0.296 | 0.317 | 0.348 | 0.330 | 0.221 | 0.369 | 0.285 | 0.286 | 0.347 | 0.372 | 0.250 | 1.000 | 0.406 | 0.435 | 0.397 | 0.329 | 0.421 | 0.349 | 0.377 | 0.354 | 0.210 | 0.243 | 0.295 | 0.295 | 0.234 | 0.275 | 0.372 | 0.410 | 0.337 | 0.322 | 0.211 | 0.153 | 0.345 |
Q6_6 | 0.290 | 0.390 | 0.302 | 0.408 | 0.456 | 0.350 | 0.294 | 0.409 | 0.332 | 0.383 | 0.428 | 0.499 | 0.476 | 0.422 | 0.430 | 0.377 | 0.421 | 0.389 | 0.423 | 0.349 | 0.326 | 0.362 | 0.268 | 0.185 | 0.334 | 0.442 | 0.335 | 0.448 | 0.420 | 0.376 | 0.378 | 0.577 | 0.595 | 0.638 | 0.560 | 0.406 | 1.000 | 0.682 | 0.690 | 0.346 | 0.395 | 0.534 | 0.519 | 0.440 | 0.249 | 0.389 | 0.406 | 0.387 | 0.209 | 0.382 | 0.440 | 0.534 | 0.413 | 0.235 | 0.060 | 0.104 | 0.445 |
Q6_7 | 0.369 | 0.392 | 0.367 | 0.394 | 0.425 | 0.363 | 0.295 | 0.489 | 0.411 | 0.434 | 0.448 | 0.527 | 0.445 | 0.481 | 0.481 | 0.441 | 0.455 | 0.484 | 0.462 | 0.379 | 0.349 | 0.371 | 0.210 | 0.158 | 0.409 | 0.511 | 0.358 | 0.483 | 0.384 | 0.406 | 0.405 | 0.559 | 0.593 | 0.668 | 0.592 | 0.435 | 0.682 | 1.000 | 0.727 | 0.401 | 0.444 | 0.558 | 0.514 | 0.450 | 0.302 | 0.383 | 0.437 | 0.409 | 0.274 | 0.394 | 0.447 | 0.503 | 0.414 | 0.271 | 0.075 | 0.151 | 0.444 |
Q6_8 | 0.312 | 0.300 | 0.309 | 0.354 | 0.389 | 0.324 | 0.287 | 0.407 | 0.332 | 0.336 | 0.442 | 0.514 | 0.425 | 0.438 | 0.444 | 0.382 | 0.413 | 0.394 | 0.401 | 0.304 | 0.323 | 0.355 | 0.191 | 0.119 | 0.350 | 0.460 | 0.351 | 0.447 | 0.388 | 0.370 | 0.346 | 0.566 | 0.631 | 0.574 | 0.640 | 0.397 | 0.690 | 0.727 | 1.000 | 0.403 | 0.416 | 0.499 | 0.477 | 0.401 | 0.235 | 0.425 | 0.424 | 0.421 | 0.196 | 0.347 | 0.436 | 0.486 | 0.405 | 0.250 | 0.057 | 0.108 | 0.457 |
Q6_9 | 0.245 | 0.266 | 0.245 | 0.290 | 0.288 | 0.276 | 0.238 | 0.310 | 0.331 | 0.311 | 0.383 | 0.402 | 0.329 | 0.442 | 0.381 | 0.276 | 0.296 | 0.332 | 0.388 | 0.362 | 0.258 | 0.314 | 0.174 | 0.110 | 0.250 | 0.405 | 0.251 | 0.363 | 0.261 | 0.339 | 0.265 | 0.280 | 0.253 | 0.227 | 0.191 | 0.329 | 0.346 | 0.401 | 0.403 | 1.000 | 0.472 | 0.469 | 0.387 | 0.355 | 0.340 | 0.273 | 0.432 | 0.451 | 0.335 | 0.365 | 0.335 | 0.342 | 0.306 | 0.359 | 0.352 | 0.239 | 0.336 |
Q6_10 | 0.309 | 0.365 | 0.284 | 0.364 | 0.368 | 0.387 | 0.337 | 0.352 | 0.280 | 0.286 | 0.374 | 0.335 | 0.256 | 0.428 | 0.390 | 0.359 | 0.380 | 0.367 | 0.408 | 0.301 | 0.350 | 0.335 | 0.298 | 0.225 | 0.397 | 0.356 | 0.382 | 0.449 | 0.364 | 0.423 | 0.371 | 0.286 | 0.312 | 0.269 | 0.299 | 0.421 | 0.395 | 0.444 | 0.416 | 0.472 | 1.000 | 0.577 | 0.431 | 0.378 | 0.300 | 0.325 | 0.422 | 0.402 | 0.360 | 0.390 | 0.455 | 0.419 | 0.397 | 0.388 | 0.198 | 0.263 | 0.428 |
Q6_11 | 0.357 | 0.422 | 0.369 | 0.460 | 0.460 | 0.486 | 0.429 | 0.406 | 0.308 | 0.441 | 0.451 | 0.476 | 0.357 | 0.529 | 0.450 | 0.388 | 0.360 | 0.471 | 0.452 | 0.417 | 0.494 | 0.423 | 0.386 | 0.272 | 0.461 | 0.492 | 0.497 | 0.564 | 0.429 | 0.415 | 0.483 | 0.369 | 0.418 | 0.415 | 0.366 | 0.349 | 0.534 | 0.558 | 0.499 | 0.469 | 0.577 | 1.000 | 0.568 | 0.505 | 0.486 | 0.471 | 0.523 | 0.493 | 0.469 | 0.441 | 0.484 | 0.477 | 0.396 | 0.366 | 0.218 | 0.378 | 0.467 |
Q7_1 | 0.458 | 0.483 | 0.449 | 0.469 | 0.510 | 0.496 | 0.342 | 0.415 | 0.379 | 0.419 | 0.526 | 0.450 | 0.413 | 0.478 | 0.503 | 0.467 | 0.376 | 0.496 | 0.495 | 0.536 | 0.472 | 0.521 | 0.414 | 0.356 | 0.488 | 0.464 | 0.506 | 0.587 | 0.436 | 0.576 | 0.481 | 0.472 | 0.461 | 0.447 | 0.357 | 0.377 | 0.519 | 0.514 | 0.477 | 0.387 | 0.431 | 0.568 | 1.000 | 0.637 | 0.447 | 0.530 | 0.558 | 0.521 | 0.408 | 0.454 | 0.631 | 0.640 | 0.533 | 0.447 | 0.195 | 0.269 | 0.632 |
Q7_2 | 0.340 | 0.387 | 0.356 | 0.476 | 0.387 | 0.415 | 0.414 | 0.369 | 0.382 | 0.497 | 0.447 | 0.440 | 0.371 | 0.437 | 0.455 | 0.373 | 0.341 | 0.448 | 0.452 | 0.426 | 0.457 | 0.416 | 0.421 | 0.413 | 0.444 | 0.497 | 0.458 | 0.461 | 0.426 | 0.433 | 0.398 | 0.300 | 0.345 | 0.313 | 0.315 | 0.354 | 0.440 | 0.450 | 0.401 | 0.355 | 0.378 | 0.505 | 0.637 | 1.000 | 0.502 | 0.572 | 0.566 | 0.517 | 0.464 | 0.514 | 0.483 | 0.492 | 0.604 | 0.378 | 0.218 | 0.368 | 0.503 |
Q7_3 | 0.247 | 0.285 | 0.289 | 0.370 | 0.279 | 0.380 | 0.452 | 0.253 | 0.301 | 0.377 | 0.334 | 0.303 | 0.170 | 0.336 | 0.265 | 0.235 | 0.281 | 0.305 | 0.376 | 0.309 | 0.384 | 0.280 | 0.439 | 0.359 | 0.402 | 0.340 | 0.416 | 0.347 | 0.289 | 0.383 | 0.412 | 0.117 | 0.237 | 0.271 | 0.189 | 0.210 | 0.249 | 0.302 | 0.235 | 0.340 | 0.300 | 0.486 | 0.447 | 0.502 | 1.000 | 0.565 | 0.545 | 0.540 | 0.732 | 0.465 | 0.308 | 0.290 | 0.410 | 0.457 | 0.324 | 0.485 | 0.333 |
Q7_4 | 0.331 | 0.342 | 0.303 | 0.487 | 0.368 | 0.418 | 0.400 | 0.296 | 0.326 | 0.393 | 0.392 | 0.357 | 0.224 | 0.332 | 0.332 | 0.291 | 0.360 | 0.386 | 0.387 | 0.329 | 0.397 | 0.300 | 0.308 | 0.304 | 0.407 | 0.360 | 0.426 | 0.435 | 0.363 | 0.446 | 0.485 | 0.220 | 0.322 | 0.295 | 0.320 | 0.243 | 0.389 | 0.383 | 0.425 | 0.273 | 0.325 | 0.471 | 0.530 | 0.572 | 0.565 | 1.000 | 0.670 | 0.525 | 0.446 | 0.507 | 0.508 | 0.464 | 0.512 | 0.373 | 0.155 | 0.360 | 0.505 |
Q7_5 | 0.398 | 0.474 | 0.406 | 0.499 | 0.418 | 0.400 | 0.409 | 0.371 | 0.413 | 0.486 | 0.542 | 0.451 | 0.281 | 0.462 | 0.473 | 0.383 | 0.432 | 0.446 | 0.503 | 0.468 | 0.402 | 0.386 | 0.363 | 0.302 | 0.470 | 0.431 | 0.438 | 0.450 | 0.422 | 0.454 | 0.482 | 0.278 | 0.344 | 0.294 | 0.265 | 0.295 | 0.406 | 0.437 | 0.424 | 0.432 | 0.422 | 0.523 | 0.558 | 0.566 | 0.545 | 0.670 | 1.000 | 0.597 | 0.569 | 0.604 | 0.556 | 0.555 | 0.578 | 0.467 | 0.299 | 0.412 | 0.506 |
Q7_6 | 0.357 | 0.384 | 0.390 | 0.473 | 0.367 | 0.394 | 0.357 | 0.363 | 0.450 | 0.391 | 0.453 | 0.428 | 0.357 | 0.463 | 0.451 | 0.386 | 0.367 | 0.412 | 0.483 | 0.399 | 0.431 | 0.377 | 0.346 | 0.292 | 0.446 | 0.415 | 0.444 | 0.399 | 0.396 | 0.394 | 0.396 | 0.289 | 0.353 | 0.333 | 0.329 | 0.295 | 0.387 | 0.409 | 0.421 | 0.451 | 0.402 | 0.493 | 0.521 | 0.517 | 0.540 | 0.525 | 0.597 | 1.000 | 0.562 | 0.546 | 0.467 | 0.476 | 0.508 | 0.473 | 0.234 | 0.487 | 0.368 |
Q7_7 | 0.287 | 0.352 | 0.377 | 0.403 | 0.368 | 0.370 | 0.425 | 0.269 | 0.347 | 0.395 | 0.347 | 0.310 | 0.202 | 0.371 | 0.331 | 0.260 | 0.333 | 0.352 | 0.429 | 0.363 | 0.442 | 0.324 | 0.469 | 0.389 | 0.422 | 0.311 | 0.386 | 0.307 | 0.335 | 0.354 | 0.410 | 0.143 | 0.152 | 0.179 | 0.142 | 0.234 | 0.209 | 0.274 | 0.196 | 0.335 | 0.360 | 0.469 | 0.408 | 0.464 | 0.732 | 0.446 | 0.569 | 0.562 | 1.000 | 0.597 | 0.385 | 0.332 | 0.459 | 0.503 | 0.378 | 0.530 | 0.287 |
Q7_8 | 0.298 | 0.394 | 0.337 | 0.436 | 0.370 | 0.328 | 0.340 | 0.359 | 0.375 | 0.409 | 0.414 | 0.368 | 0.284 | 0.398 | 0.429 | 0.329 | 0.394 | 0.415 | 0.479 | 0.384 | 0.327 | 0.335 | 0.314 | 0.315 | 0.395 | 0.429 | 0.424 | 0.421 | 0.416 | 0.371 | 0.453 | 0.185 | 0.217 | 0.214 | 0.217 | 0.275 | 0.382 | 0.394 | 0.347 | 0.365 | 0.390 | 0.441 | 0.454 | 0.514 | 0.465 | 0.507 | 0.604 | 0.546 | 0.597 | 1.000 | 0.515 | 0.465 | 0.620 | 0.391 | 0.255 | 0.393 | 0.389 |
Q7_9 | 0.527 | 0.471 | 0.488 | 0.521 | 0.491 | 0.448 | 0.334 | 0.434 | 0.409 | 0.385 | 0.435 | 0.397 | 0.388 | 0.490 | 0.448 | 0.432 | 0.432 | 0.479 | 0.486 | 0.490 | 0.436 | 0.462 | 0.345 | 0.284 | 0.454 | 0.369 | 0.434 | 0.521 | 0.398 | 0.526 | 0.486 | 0.378 | 0.399 | 0.337 | 0.328 | 0.372 | 0.440 | 0.447 | 0.436 | 0.335 | 0.455 | 0.484 | 0.631 | 0.483 | 0.308 | 0.508 | 0.556 | 0.467 | 0.385 | 0.515 | 1.000 | 0.693 | 0.567 | 0.375 | 0.188 | 0.277 | 0.593 |
Q7_10 | 0.495 | 0.505 | 0.479 | 0.516 | 0.550 | 0.497 | 0.312 | 0.487 | 0.457 | 0.432 | 0.481 | 0.397 | 0.455 | 0.421 | 0.492 | 0.440 | 0.452 | 0.550 | 0.507 | 0.423 | 0.416 | 0.421 | 0.322 | 0.260 | 0.453 | 0.372 | 0.422 | 0.500 | 0.417 | 0.472 | 0.455 | 0.389 | 0.435 | 0.404 | 0.394 | 0.410 | 0.534 | 0.503 | 0.486 | 0.342 | 0.419 | 0.477 | 0.640 | 0.492 | 0.290 | 0.464 | 0.555 | 0.476 | 0.332 | 0.465 | 0.693 | 1.000 | 0.538 | 0.323 | 0.127 | 0.190 | 0.680 |
Q7_11 | 0.423 | 0.407 | 0.472 | 0.517 | 0.347 | 0.376 | 0.322 | 0.397 | 0.463 | 0.484 | 0.469 | 0.275 | 0.257 | 0.380 | 0.487 | 0.385 | 0.403 | 0.470 | 0.479 | 0.462 | 0.335 | 0.340 | 0.356 | 0.365 | 0.426 | 0.403 | 0.421 | 0.433 | 0.414 | 0.450 | 0.432 | 0.237 | 0.286 | 0.249 | 0.304 | 0.337 | 0.413 | 0.414 | 0.405 | 0.306 | 0.397 | 0.396 | 0.533 | 0.604 | 0.410 | 0.512 | 0.578 | 0.508 | 0.459 | 0.620 | 0.567 | 0.538 | 1.000 | 0.519 | 0.260 | 0.344 | 0.446 |
Q7_12 | 0.307 | 0.281 | 0.345 | 0.334 | 0.282 | 0.300 | 0.266 | 0.246 | 0.320 | 0.309 | 0.385 | 0.259 | 0.266 | 0.360 | 0.326 | 0.256 | 0.272 | 0.272 | 0.369 | 0.382 | 0.254 | 0.293 | 0.308 | 0.333 | 0.348 | 0.298 | 0.360 | 0.342 | 0.298 | 0.454 | 0.396 | 0.256 | 0.242 | 0.217 | 0.162 | 0.322 | 0.235 | 0.271 | 0.250 | 0.359 | 0.388 | 0.366 | 0.447 | 0.378 | 0.457 | 0.373 | 0.467 | 0.473 | 0.503 | 0.391 | 0.375 | 0.323 | 0.519 | 1.000 | 0.483 | 0.449 | 0.366 |
Q7_13 | 0.127 | 0.129 | 0.148 | 0.134 | 0.085 | 0.225 | 0.199 | 0.082 | 0.129 | 0.158 | 0.204 | 0.103 | 0.074 | 0.217 | 0.137 | 0.102 | 0.097 | 0.096 | 0.130 | 0.156 | 0.154 | 0.122 | 0.145 | 0.150 | 0.140 | 0.135 | 0.152 | 0.103 | 0.040 | 0.317 | 0.200 | 0.124 | 0.095 | 0.095 | 0.022 | 0.211 | 0.060 | 0.075 | 0.057 | 0.352 | 0.198 | 0.218 | 0.195 | 0.218 | 0.324 | 0.155 | 0.299 | 0.234 | 0.378 | 0.255 | 0.188 | 0.127 | 0.260 | 0.483 | 1.000 | 0.424 | 0.138 |
Q7_14 | 0.218 | 0.197 | 0.211 | 0.308 | 0.173 | 0.400 | 0.336 | 0.156 | 0.198 | 0.316 | 0.292 | 0.180 | 0.096 | 0.271 | 0.200 | 0.163 | 0.149 | 0.271 | 0.248 | 0.256 | 0.327 | 0.242 | 0.370 | 0.348 | 0.372 | 0.211 | 0.323 | 0.265 | 0.280 | 0.279 | 0.354 | 0.080 | 0.150 | 0.164 | 0.096 | 0.153 | 0.104 | 0.151 | 0.108 | 0.239 | 0.263 | 0.378 | 0.269 | 0.368 | 0.485 | 0.360 | 0.412 | 0.487 | 0.530 | 0.393 | 0.277 | 0.190 | 0.344 | 0.449 | 0.424 | 1.000 | 0.285 |
Q7_15 | 0.445 | 0.454 | 0.411 | 0.477 | 0.474 | 0.466 | 0.284 | 0.398 | 0.341 | 0.440 | 0.508 | 0.371 | 0.315 | 0.427 | 0.447 | 0.422 | 0.399 | 0.513 | 0.458 | 0.435 | 0.404 | 0.435 | 0.310 | 0.266 | 0.404 | 0.331 | 0.380 | 0.506 | 0.344 | 0.422 | 0.447 | 0.364 | 0.344 | 0.346 | 0.278 | 0.345 | 0.445 | 0.444 | 0.457 | 0.336 | 0.428 | 0.467 | 0.632 | 0.503 | 0.333 | 0.505 | 0.506 | 0.368 | 0.287 | 0.389 | 0.593 | 0.680 | 0.446 | 0.366 | 0.138 | 0.285 | 1.000 |
# Polychoric Correlation
corr.pc <- polychoric(dat)
Warning in cor.smooth(mat): Matrix was not positive definite, smoothing was done
kable(corr.pc$rho,digits=3,format = "html")%>%
kable_styling(full_width = T)%>%
scroll_box(width="100%", height="500px")
Q4_1 | Q4_2 | Q4_3 | Q4_4 | Q4_5 | Q4_6 | Q4_7 | Q4_8 | Q4_9 | Q4_10 | Q4_11 | Q4_12 | Q4_13 | Q4_14 | Q4_15 | Q4_16 | Q4_17 | Q4_18 | Q4_19 | Q5_1 | Q5_2 | Q5_3 | Q5_4 | Q5_5 | Q5_6 | Q5_7 | Q5_8 | Q5_9 | Q5_10 | Q5_11 | Q5_12 | Q6_1 | Q6_2 | Q6_3 | Q6_4 | Q6_5 | Q6_6 | Q6_7 | Q6_8 | Q6_9 | Q6_10 | Q6_11 | Q7_1 | Q7_2 | Q7_3 | Q7_4 | Q7_5 | Q7_6 | Q7_7 | Q7_8 | Q7_9 | Q7_10 | Q7_11 | Q7_12 | Q7_13 | Q7_14 | Q7_15 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Q4_1 | 1.000 | 0.701 | 0.761 | 0.752 | 0.574 | 0.522 | 0.349 | 0.655 | 0.491 | 0.643 | 0.648 | 0.471 | 0.500 | 0.607 | 0.602 | 0.606 | 0.533 | 0.734 | 0.558 | 0.474 | 0.377 | 0.407 | 0.381 | 0.319 | 0.438 | 0.340 | 0.347 | 0.487 | 0.404 | 0.476 | 0.364 | 0.370 | 0.325 | 0.304 | 0.307 | 0.300 | 0.356 | 0.434 | 0.370 | 0.288 | 0.345 | 0.404 | 0.516 | 0.390 | 0.266 | 0.369 | 0.444 | 0.406 | 0.334 | 0.332 | 0.586 | 0.570 | 0.484 | 0.351 | 0.134 | 0.229 | 0.502 |
Q4_2 | 0.701 | 1.000 | 0.721 | 0.717 | 0.731 | 0.551 | 0.380 | 0.693 | 0.576 | 0.629 | 0.632 | 0.557 | 0.615 | 0.534 | 0.663 | 0.565 | 0.591 | 0.804 | 0.624 | 0.530 | 0.434 | 0.472 | 0.384 | 0.338 | 0.479 | 0.351 | 0.423 | 0.512 | 0.455 | 0.532 | 0.421 | 0.351 | 0.372 | 0.337 | 0.285 | 0.400 | 0.475 | 0.468 | 0.359 | 0.318 | 0.410 | 0.483 | 0.557 | 0.453 | 0.315 | 0.388 | 0.546 | 0.442 | 0.411 | 0.449 | 0.537 | 0.591 | 0.482 | 0.314 | 0.137 | 0.217 | 0.522 |
Q4_3 | 0.761 | 0.721 | 1.000 | 0.766 | 0.550 | 0.463 | 0.347 | 0.681 | 0.579 | 0.676 | 0.632 | 0.409 | 0.451 | 0.502 | 0.603 | 0.571 | 0.542 | 0.694 | 0.640 | 0.485 | 0.387 | 0.400 | 0.357 | 0.328 | 0.488 | 0.348 | 0.388 | 0.505 | 0.385 | 0.538 | 0.323 | 0.393 | 0.313 | 0.317 | 0.284 | 0.360 | 0.363 | 0.432 | 0.357 | 0.290 | 0.319 | 0.415 | 0.504 | 0.398 | 0.308 | 0.338 | 0.454 | 0.443 | 0.411 | 0.379 | 0.546 | 0.549 | 0.535 | 0.374 | 0.154 | 0.230 | 0.463 |
Q4_4 | 0.752 | 0.717 | 0.766 | 1.000 | 0.590 | 0.544 | 0.469 | 0.690 | 0.572 | 0.735 | 0.642 | 0.521 | 0.467 | 0.537 | 0.589 | 0.592 | 0.591 | 0.749 | 0.594 | 0.474 | 0.401 | 0.399 | 0.414 | 0.399 | 0.523 | 0.446 | 0.422 | 0.485 | 0.462 | 0.433 | 0.481 | 0.305 | 0.365 | 0.384 | 0.274 | 0.346 | 0.514 | 0.465 | 0.416 | 0.345 | 0.399 | 0.506 | 0.536 | 0.532 | 0.386 | 0.543 | 0.552 | 0.527 | 0.431 | 0.474 | 0.579 | 0.597 | 0.592 | 0.351 | 0.142 | 0.313 | 0.539 |
Q4_5 | 0.574 | 0.731 | 0.550 | 0.590 | 1.000 | 0.581 | 0.357 | 0.590 | 0.474 | 0.576 | 0.602 | 0.576 | 0.635 | 0.521 | 0.618 | 0.516 | 0.570 | 0.685 | 0.610 | 0.507 | 0.444 | 0.492 | 0.412 | 0.318 | 0.440 | 0.421 | 0.466 | 0.600 | 0.461 | 0.558 | 0.465 | 0.400 | 0.426 | 0.440 | 0.329 | 0.322 | 0.536 | 0.501 | 0.451 | 0.338 | 0.419 | 0.518 | 0.578 | 0.446 | 0.318 | 0.420 | 0.474 | 0.424 | 0.419 | 0.424 | 0.559 | 0.621 | 0.409 | 0.315 | 0.078 | 0.172 | 0.543 |
Q4_6 | 0.522 | 0.551 | 0.463 | 0.544 | 0.581 | 1.000 | 0.640 | 0.477 | 0.377 | 0.529 | 0.498 | 0.442 | 0.396 | 0.451 | 0.502 | 0.516 | 0.448 | 0.563 | 0.500 | 0.413 | 0.523 | 0.486 | 0.431 | 0.359 | 0.501 | 0.419 | 0.477 | 0.545 | 0.383 | 0.457 | 0.466 | 0.376 | 0.490 | 0.425 | 0.338 | 0.314 | 0.413 | 0.417 | 0.369 | 0.313 | 0.432 | 0.529 | 0.552 | 0.466 | 0.413 | 0.456 | 0.434 | 0.432 | 0.435 | 0.360 | 0.497 | 0.563 | 0.426 | 0.329 | 0.251 | 0.431 | 0.523 |
Q4_7 | 0.349 | 0.380 | 0.347 | 0.469 | 0.357 | 0.640 | 1.000 | 0.334 | 0.289 | 0.442 | 0.460 | 0.349 | 0.176 | 0.397 | 0.319 | 0.399 | 0.325 | 0.351 | 0.405 | 0.373 | 0.423 | 0.341 | 0.431 | 0.326 | 0.385 | 0.434 | 0.448 | 0.405 | 0.385 | 0.377 | 0.431 | 0.253 | 0.321 | 0.284 | 0.300 | 0.186 | 0.360 | 0.338 | 0.343 | 0.279 | 0.376 | 0.473 | 0.389 | 0.464 | 0.482 | 0.439 | 0.444 | 0.383 | 0.461 | 0.358 | 0.369 | 0.363 | 0.363 | 0.278 | 0.217 | 0.337 | 0.332 |
Q4_8 | 0.655 | 0.693 | 0.681 | 0.690 | 0.590 | 0.477 | 0.334 | 1.000 | 0.652 | 0.654 | 0.636 | 0.565 | 0.583 | 0.572 | 0.650 | 0.529 | 0.627 | 0.719 | 0.693 | 0.467 | 0.398 | 0.452 | 0.301 | 0.247 | 0.408 | 0.351 | 0.423 | 0.486 | 0.382 | 0.450 | 0.399 | 0.355 | 0.366 | 0.425 | 0.347 | 0.343 | 0.481 | 0.556 | 0.461 | 0.361 | 0.399 | 0.463 | 0.476 | 0.429 | 0.281 | 0.333 | 0.420 | 0.419 | 0.316 | 0.411 | 0.490 | 0.552 | 0.461 | 0.271 | 0.085 | 0.166 | 0.446 |
Q4_9 | 0.491 | 0.576 | 0.579 | 0.572 | 0.474 | 0.377 | 0.289 | 0.652 | 1.000 | 0.540 | 0.594 | 0.519 | 0.548 | 0.502 | 0.600 | 0.475 | 0.543 | 0.613 | 0.766 | 0.438 | 0.390 | 0.413 | 0.267 | 0.284 | 0.414 | 0.329 | 0.359 | 0.382 | 0.316 | 0.451 | 0.450 | 0.328 | 0.336 | 0.324 | 0.319 | 0.305 | 0.394 | 0.474 | 0.384 | 0.375 | 0.308 | 0.350 | 0.439 | 0.451 | 0.332 | 0.370 | 0.470 | 0.506 | 0.392 | 0.422 | 0.467 | 0.519 | 0.534 | 0.360 | 0.135 | 0.213 | 0.384 |
Q4_10 | 0.643 | 0.629 | 0.676 | 0.735 | 0.576 | 0.529 | 0.442 | 0.654 | 0.540 | 1.000 | 0.642 | 0.519 | 0.456 | 0.497 | 0.611 | 0.568 | 0.552 | 0.721 | 0.640 | 0.507 | 0.324 | 0.361 | 0.375 | 0.376 | 0.436 | 0.442 | 0.418 | 0.538 | 0.446 | 0.459 | 0.426 | 0.341 | 0.360 | 0.436 | 0.332 | 0.322 | 0.486 | 0.540 | 0.418 | 0.378 | 0.334 | 0.502 | 0.485 | 0.572 | 0.419 | 0.440 | 0.545 | 0.449 | 0.441 | 0.458 | 0.442 | 0.521 | 0.559 | 0.333 | 0.176 | 0.338 | 0.506 |
Q4_11 | 0.648 | 0.632 | 0.632 | 0.642 | 0.602 | 0.498 | 0.460 | 0.636 | 0.594 | 0.642 | 1.000 | 0.634 | 0.588 | 0.600 | 0.653 | 0.619 | 0.595 | 0.724 | 0.738 | 0.522 | 0.441 | 0.454 | 0.353 | 0.302 | 0.473 | 0.491 | 0.457 | 0.585 | 0.550 | 0.512 | 0.437 | 0.400 | 0.397 | 0.396 | 0.370 | 0.414 | 0.500 | 0.520 | 0.510 | 0.437 | 0.413 | 0.504 | 0.589 | 0.511 | 0.367 | 0.435 | 0.599 | 0.512 | 0.399 | 0.459 | 0.485 | 0.539 | 0.544 | 0.432 | 0.226 | 0.312 | 0.566 |
Q4_12 | 0.471 | 0.557 | 0.409 | 0.521 | 0.576 | 0.442 | 0.349 | 0.565 | 0.519 | 0.519 | 0.634 | 1.000 | 0.814 | 0.608 | 0.568 | 0.490 | 0.562 | 0.632 | 0.603 | 0.454 | 0.434 | 0.481 | 0.290 | 0.213 | 0.370 | 0.491 | 0.415 | 0.489 | 0.463 | 0.411 | 0.404 | 0.520 | 0.505 | 0.517 | 0.416 | 0.421 | 0.599 | 0.610 | 0.600 | 0.467 | 0.392 | 0.551 | 0.520 | 0.525 | 0.365 | 0.408 | 0.521 | 0.485 | 0.375 | 0.421 | 0.458 | 0.454 | 0.342 | 0.304 | 0.110 | 0.193 | 0.428 |
Q4_13 | 0.500 | 0.615 | 0.451 | 0.467 | 0.635 | 0.396 | 0.176 | 0.583 | 0.548 | 0.456 | 0.588 | 0.814 | 1.000 | 0.611 | 0.577 | 0.458 | 0.521 | 0.698 | 0.619 | 0.514 | 0.446 | 0.503 | 0.236 | 0.179 | 0.361 | 0.476 | 0.356 | 0.496 | 0.463 | 0.452 | 0.427 | 0.561 | 0.506 | 0.490 | 0.427 | 0.463 | 0.575 | 0.574 | 0.521 | 0.445 | 0.315 | 0.452 | 0.529 | 0.485 | 0.226 | 0.288 | 0.385 | 0.471 | 0.258 | 0.359 | 0.488 | 0.558 | 0.352 | 0.345 | 0.062 | 0.083 | 0.398 |
Q4_14 | 0.607 | 0.534 | 0.502 | 0.537 | 0.521 | 0.451 | 0.397 | 0.572 | 0.502 | 0.497 | 0.600 | 0.608 | 0.611 | 1.000 | 0.742 | 0.655 | 0.502 | 0.633 | 0.580 | 0.519 | 0.469 | 0.519 | 0.343 | 0.284 | 0.509 | 0.445 | 0.417 | 0.560 | 0.406 | 0.516 | 0.451 | 0.505 | 0.430 | 0.431 | 0.411 | 0.401 | 0.501 | 0.567 | 0.518 | 0.508 | 0.486 | 0.576 | 0.535 | 0.484 | 0.364 | 0.365 | 0.507 | 0.519 | 0.424 | 0.431 | 0.546 | 0.491 | 0.433 | 0.411 | 0.240 | 0.278 | 0.487 |
Q4_15 | 0.602 | 0.663 | 0.603 | 0.589 | 0.618 | 0.502 | 0.319 | 0.650 | 0.600 | 0.611 | 0.653 | 0.568 | 0.577 | 0.742 | 1.000 | 0.774 | 0.671 | 0.735 | 0.659 | 0.526 | 0.451 | 0.514 | 0.401 | 0.320 | 0.551 | 0.500 | 0.478 | 0.593 | 0.505 | 0.517 | 0.504 | 0.421 | 0.408 | 0.416 | 0.384 | 0.364 | 0.508 | 0.557 | 0.507 | 0.432 | 0.435 | 0.503 | 0.566 | 0.521 | 0.294 | 0.373 | 0.532 | 0.519 | 0.384 | 0.484 | 0.503 | 0.553 | 0.557 | 0.370 | 0.145 | 0.207 | 0.501 |
Q4_16 | 0.606 | 0.565 | 0.571 | 0.592 | 0.516 | 0.516 | 0.399 | 0.529 | 0.475 | 0.568 | 0.619 | 0.490 | 0.458 | 0.655 | 0.774 | 1.000 | 0.669 | 0.646 | 0.594 | 0.461 | 0.445 | 0.524 | 0.388 | 0.356 | 0.554 | 0.468 | 0.443 | 0.557 | 0.463 | 0.497 | 0.473 | 0.499 | 0.492 | 0.448 | 0.417 | 0.246 | 0.462 | 0.513 | 0.447 | 0.325 | 0.408 | 0.437 | 0.524 | 0.426 | 0.253 | 0.328 | 0.431 | 0.437 | 0.288 | 0.364 | 0.486 | 0.506 | 0.438 | 0.291 | 0.106 | 0.160 | 0.483 |
Q4_17 | 0.533 | 0.591 | 0.542 | 0.591 | 0.570 | 0.448 | 0.325 | 0.627 | 0.543 | 0.552 | 0.595 | 0.562 | 0.521 | 0.502 | 0.671 | 0.669 | 1.000 | 0.691 | 0.601 | 0.440 | 0.381 | 0.421 | 0.267 | 0.190 | 0.421 | 0.418 | 0.355 | 0.404 | 0.469 | 0.451 | 0.382 | 0.394 | 0.350 | 0.427 | 0.354 | 0.313 | 0.498 | 0.525 | 0.469 | 0.344 | 0.436 | 0.408 | 0.431 | 0.397 | 0.318 | 0.407 | 0.490 | 0.420 | 0.382 | 0.450 | 0.491 | 0.512 | 0.470 | 0.301 | 0.090 | 0.160 | 0.455 |
Q4_18 | 0.734 | 0.804 | 0.694 | 0.749 | 0.685 | 0.563 | 0.351 | 0.719 | 0.613 | 0.721 | 0.724 | 0.632 | 0.698 | 0.633 | 0.735 | 0.646 | 0.691 | 1.000 | 0.731 | 0.547 | 0.483 | 0.479 | 0.365 | 0.369 | 0.585 | 0.452 | 0.495 | 0.605 | 0.587 | 0.505 | 0.480 | 0.380 | 0.361 | 0.406 | 0.325 | 0.377 | 0.472 | 0.566 | 0.454 | 0.390 | 0.420 | 0.535 | 0.569 | 0.520 | 0.336 | 0.440 | 0.506 | 0.469 | 0.406 | 0.465 | 0.541 | 0.626 | 0.562 | 0.312 | 0.096 | 0.295 | 0.584 |
Q4_19 | 0.558 | 0.624 | 0.640 | 0.594 | 0.610 | 0.500 | 0.405 | 0.693 | 0.766 | 0.640 | 0.738 | 0.603 | 0.619 | 0.580 | 0.659 | 0.594 | 0.601 | 0.731 | 1.000 | 0.528 | 0.501 | 0.522 | 0.357 | 0.307 | 0.530 | 0.461 | 0.468 | 0.586 | 0.462 | 0.522 | 0.494 | 0.417 | 0.404 | 0.416 | 0.391 | 0.328 | 0.505 | 0.541 | 0.466 | 0.449 | 0.456 | 0.505 | 0.561 | 0.507 | 0.422 | 0.431 | 0.553 | 0.537 | 0.490 | 0.542 | 0.547 | 0.569 | 0.553 | 0.419 | 0.134 | 0.266 | 0.515 |
Q5_1 | 0.474 | 0.530 | 0.485 | 0.474 | 0.507 | 0.413 | 0.373 | 0.467 | 0.438 | 0.507 | 0.522 | 0.454 | 0.514 | 0.519 | 0.526 | 0.461 | 0.440 | 0.547 | 0.528 | 1.000 | 0.555 | 0.631 | 0.438 | 0.366 | 0.550 | 0.432 | 0.514 | 0.608 | 0.530 | 0.562 | 0.517 | 0.381 | 0.315 | 0.291 | 0.235 | 0.360 | 0.424 | 0.432 | 0.352 | 0.418 | 0.330 | 0.465 | 0.593 | 0.474 | 0.334 | 0.361 | 0.515 | 0.441 | 0.407 | 0.419 | 0.542 | 0.474 | 0.530 | 0.423 | 0.167 | 0.270 | 0.487 |
Q5_2 | 0.377 | 0.434 | 0.387 | 0.401 | 0.444 | 0.523 | 0.423 | 0.398 | 0.390 | 0.324 | 0.441 | 0.434 | 0.446 | 0.469 | 0.451 | 0.445 | 0.381 | 0.483 | 0.501 | 0.555 | 1.000 | 0.707 | 0.503 | 0.447 | 0.659 | 0.443 | 0.578 | 0.515 | 0.485 | 0.411 | 0.544 | 0.379 | 0.391 | 0.383 | 0.404 | 0.311 | 0.396 | 0.403 | 0.377 | 0.300 | 0.377 | 0.533 | 0.511 | 0.484 | 0.384 | 0.419 | 0.432 | 0.459 | 0.484 | 0.341 | 0.475 | 0.474 | 0.359 | 0.258 | 0.164 | 0.327 | 0.444 |
Q5_3 | 0.407 | 0.472 | 0.400 | 0.399 | 0.492 | 0.486 | 0.341 | 0.452 | 0.413 | 0.361 | 0.454 | 0.481 | 0.503 | 0.519 | 0.514 | 0.524 | 0.421 | 0.479 | 0.522 | 0.631 | 0.707 | 1.000 | 0.569 | 0.441 | 0.671 | 0.427 | 0.625 | 0.631 | 0.487 | 0.536 | 0.538 | 0.453 | 0.369 | 0.357 | 0.345 | 0.298 | 0.427 | 0.424 | 0.410 | 0.365 | 0.373 | 0.469 | 0.576 | 0.471 | 0.300 | 0.332 | 0.429 | 0.423 | 0.369 | 0.374 | 0.512 | 0.475 | 0.388 | 0.316 | 0.129 | 0.246 | 0.486 |
Q5_4 | 0.381 | 0.384 | 0.357 | 0.414 | 0.412 | 0.431 | 0.431 | 0.301 | 0.267 | 0.375 | 0.353 | 0.290 | 0.236 | 0.343 | 0.401 | 0.388 | 0.267 | 0.365 | 0.357 | 0.438 | 0.503 | 0.569 | 1.000 | 0.837 | 0.632 | 0.390 | 0.585 | 0.488 | 0.433 | 0.417 | 0.486 | 0.221 | 0.267 | 0.290 | 0.205 | 0.243 | 0.302 | 0.227 | 0.210 | 0.223 | 0.320 | 0.415 | 0.451 | 0.444 | 0.478 | 0.324 | 0.389 | 0.380 | 0.532 | 0.364 | 0.371 | 0.367 | 0.373 | 0.341 | 0.168 | 0.379 | 0.344 |
Q5_5 | 0.319 | 0.338 | 0.328 | 0.399 | 0.318 | 0.359 | 0.326 | 0.247 | 0.284 | 0.376 | 0.302 | 0.213 | 0.179 | 0.284 | 0.320 | 0.356 | 0.190 | 0.369 | 0.307 | 0.366 | 0.447 | 0.441 | 0.837 | 1.000 | 0.628 | 0.367 | 0.577 | 0.446 | 0.343 | 0.408 | 0.433 | 0.141 | 0.208 | 0.228 | 0.180 | 0.226 | 0.205 | 0.180 | 0.140 | 0.153 | 0.237 | 0.289 | 0.394 | 0.434 | 0.389 | 0.315 | 0.316 | 0.323 | 0.429 | 0.349 | 0.313 | 0.311 | 0.373 | 0.355 | 0.174 | 0.363 | 0.300 |
Q5_6 | 0.438 | 0.479 | 0.488 | 0.523 | 0.440 | 0.501 | 0.385 | 0.408 | 0.414 | 0.436 | 0.473 | 0.370 | 0.361 | 0.509 | 0.551 | 0.554 | 0.421 | 0.585 | 0.530 | 0.550 | 0.659 | 0.671 | 0.632 | 0.628 | 1.000 | 0.561 | 0.717 | 0.632 | 0.488 | 0.487 | 0.570 | 0.305 | 0.373 | 0.400 | 0.331 | 0.352 | 0.386 | 0.464 | 0.408 | 0.289 | 0.442 | 0.495 | 0.538 | 0.463 | 0.423 | 0.435 | 0.510 | 0.488 | 0.470 | 0.426 | 0.506 | 0.519 | 0.481 | 0.374 | 0.150 | 0.376 | 0.452 |
Q5_7 | 0.340 | 0.351 | 0.348 | 0.446 | 0.421 | 0.419 | 0.434 | 0.351 | 0.329 | 0.442 | 0.491 | 0.491 | 0.476 | 0.445 | 0.500 | 0.468 | 0.418 | 0.452 | 0.461 | 0.432 | 0.443 | 0.427 | 0.390 | 0.367 | 0.561 | 1.000 | 0.572 | 0.627 | 0.576 | 0.460 | 0.475 | 0.429 | 0.499 | 0.520 | 0.396 | 0.374 | 0.514 | 0.590 | 0.533 | 0.467 | 0.399 | 0.541 | 0.520 | 0.546 | 0.384 | 0.394 | 0.468 | 0.453 | 0.341 | 0.457 | 0.419 | 0.420 | 0.452 | 0.325 | 0.151 | 0.215 | 0.369 |
Q5_8 | 0.347 | 0.423 | 0.388 | 0.422 | 0.466 | 0.477 | 0.448 | 0.423 | 0.359 | 0.418 | 0.457 | 0.415 | 0.356 | 0.417 | 0.478 | 0.443 | 0.355 | 0.495 | 0.468 | 0.514 | 0.578 | 0.625 | 0.585 | 0.577 | 0.717 | 0.572 | 1.000 | 0.693 | 0.532 | 0.520 | 0.534 | 0.325 | 0.378 | 0.429 | 0.321 | 0.411 | 0.392 | 0.399 | 0.399 | 0.291 | 0.421 | 0.534 | 0.553 | 0.496 | 0.440 | 0.460 | 0.465 | 0.488 | 0.426 | 0.464 | 0.473 | 0.472 | 0.460 | 0.385 | 0.169 | 0.344 | 0.422 |
Q5_9 | 0.487 | 0.512 | 0.505 | 0.485 | 0.600 | 0.545 | 0.405 | 0.486 | 0.382 | 0.538 | 0.585 | 0.489 | 0.496 | 0.560 | 0.593 | 0.557 | 0.404 | 0.605 | 0.586 | 0.608 | 0.515 | 0.631 | 0.488 | 0.446 | 0.632 | 0.627 | 0.693 | 1.000 | 0.627 | 0.599 | 0.568 | 0.498 | 0.494 | 0.511 | 0.390 | 0.389 | 0.519 | 0.550 | 0.510 | 0.421 | 0.502 | 0.620 | 0.645 | 0.512 | 0.379 | 0.478 | 0.498 | 0.444 | 0.344 | 0.463 | 0.577 | 0.557 | 0.496 | 0.376 | 0.103 | 0.278 | 0.565 |
Q5_10 | 0.404 | 0.455 | 0.385 | 0.462 | 0.461 | 0.383 | 0.385 | 0.382 | 0.316 | 0.446 | 0.550 | 0.463 | 0.463 | 0.406 | 0.505 | 0.463 | 0.469 | 0.587 | 0.462 | 0.530 | 0.485 | 0.487 | 0.433 | 0.343 | 0.488 | 0.576 | 0.532 | 0.627 | 1.000 | 0.498 | 0.470 | 0.345 | 0.337 | 0.423 | 0.351 | 0.283 | 0.525 | 0.462 | 0.458 | 0.328 | 0.398 | 0.464 | 0.500 | 0.476 | 0.295 | 0.405 | 0.473 | 0.446 | 0.386 | 0.459 | 0.454 | 0.498 | 0.478 | 0.322 | 0.039 | 0.284 | 0.397 |
Q5_11 | 0.476 | 0.532 | 0.538 | 0.433 | 0.558 | 0.457 | 0.377 | 0.450 | 0.451 | 0.459 | 0.512 | 0.411 | 0.452 | 0.516 | 0.517 | 0.497 | 0.451 | 0.505 | 0.522 | 0.562 | 0.411 | 0.536 | 0.417 | 0.408 | 0.487 | 0.460 | 0.520 | 0.599 | 0.498 | 1.000 | 0.549 | 0.412 | 0.428 | 0.384 | 0.332 | 0.425 | 0.440 | 0.461 | 0.422 | 0.380 | 0.478 | 0.461 | 0.637 | 0.479 | 0.432 | 0.491 | 0.501 | 0.442 | 0.423 | 0.419 | 0.581 | 0.528 | 0.507 | 0.510 | 0.353 | 0.309 | 0.473 |
Q5_12 | 0.364 | 0.421 | 0.323 | 0.481 | 0.465 | 0.466 | 0.431 | 0.399 | 0.450 | 0.426 | 0.437 | 0.404 | 0.427 | 0.451 | 0.504 | 0.473 | 0.382 | 0.480 | 0.494 | 0.517 | 0.544 | 0.538 | 0.486 | 0.433 | 0.570 | 0.475 | 0.534 | 0.568 | 0.470 | 0.549 | 1.000 | 0.343 | 0.483 | 0.411 | 0.324 | 0.331 | 0.453 | 0.460 | 0.402 | 0.314 | 0.400 | 0.521 | 0.536 | 0.429 | 0.430 | 0.520 | 0.515 | 0.423 | 0.441 | 0.485 | 0.542 | 0.521 | 0.475 | 0.414 | 0.217 | 0.349 | 0.494 |
Q6_1 | 0.370 | 0.351 | 0.393 | 0.305 | 0.400 | 0.376 | 0.253 | 0.355 | 0.328 | 0.341 | 0.400 | 0.520 | 0.561 | 0.505 | 0.421 | 0.499 | 0.394 | 0.380 | 0.417 | 0.381 | 0.379 | 0.453 | 0.221 | 0.141 | 0.305 | 0.429 | 0.325 | 0.498 | 0.345 | 0.412 | 0.343 | 1.000 | 0.788 | 0.753 | 0.663 | 0.380 | 0.675 | 0.671 | 0.666 | 0.352 | 0.351 | 0.444 | 0.572 | 0.384 | 0.142 | 0.277 | 0.344 | 0.366 | 0.166 | 0.231 | 0.478 | 0.470 | 0.308 | 0.319 | 0.134 | 0.071 | 0.464 |
Q6_2 | 0.325 | 0.372 | 0.313 | 0.365 | 0.426 | 0.490 | 0.321 | 0.366 | 0.336 | 0.360 | 0.397 | 0.505 | 0.506 | 0.430 | 0.408 | 0.492 | 0.350 | 0.361 | 0.404 | 0.315 | 0.391 | 0.369 | 0.267 | 0.208 | 0.373 | 0.499 | 0.378 | 0.494 | 0.337 | 0.428 | 0.483 | 0.788 | 1.000 | 0.803 | 0.787 | 0.429 | 0.671 | 0.669 | 0.707 | 0.298 | 0.354 | 0.476 | 0.523 | 0.405 | 0.261 | 0.361 | 0.392 | 0.399 | 0.159 | 0.252 | 0.454 | 0.486 | 0.333 | 0.256 | 0.081 | 0.145 | 0.388 |
Q6_3 | 0.304 | 0.337 | 0.317 | 0.384 | 0.440 | 0.425 | 0.284 | 0.425 | 0.324 | 0.436 | 0.396 | 0.517 | 0.490 | 0.431 | 0.416 | 0.448 | 0.427 | 0.406 | 0.416 | 0.291 | 0.383 | 0.357 | 0.290 | 0.228 | 0.400 | 0.520 | 0.429 | 0.511 | 0.423 | 0.384 | 0.411 | 0.753 | 0.803 | 1.000 | 0.743 | 0.459 | 0.737 | 0.767 | 0.664 | 0.295 | 0.316 | 0.492 | 0.535 | 0.391 | 0.319 | 0.349 | 0.361 | 0.408 | 0.212 | 0.255 | 0.412 | 0.481 | 0.318 | 0.230 | 0.073 | 0.163 | 0.415 |
Q6_4 | 0.307 | 0.285 | 0.284 | 0.274 | 0.329 | 0.338 | 0.300 | 0.347 | 0.319 | 0.332 | 0.370 | 0.416 | 0.427 | 0.411 | 0.384 | 0.417 | 0.354 | 0.325 | 0.391 | 0.235 | 0.404 | 0.345 | 0.205 | 0.180 | 0.331 | 0.396 | 0.321 | 0.390 | 0.351 | 0.332 | 0.324 | 0.663 | 0.787 | 0.743 | 1.000 | 0.310 | 0.638 | 0.664 | 0.719 | 0.226 | 0.338 | 0.422 | 0.403 | 0.361 | 0.208 | 0.360 | 0.301 | 0.368 | 0.140 | 0.239 | 0.373 | 0.448 | 0.349 | 0.165 | 0.003 | 0.075 | 0.311 |
Q6_5 | 0.300 | 0.400 | 0.360 | 0.346 | 0.322 | 0.314 | 0.186 | 0.343 | 0.305 | 0.322 | 0.414 | 0.421 | 0.463 | 0.401 | 0.364 | 0.246 | 0.313 | 0.377 | 0.328 | 0.360 | 0.311 | 0.298 | 0.243 | 0.226 | 0.352 | 0.374 | 0.411 | 0.389 | 0.283 | 0.425 | 0.331 | 0.380 | 0.429 | 0.459 | 0.310 | 1.000 | 0.486 | 0.498 | 0.466 | 0.386 | 0.477 | 0.404 | 0.455 | 0.428 | 0.237 | 0.291 | 0.341 | 0.351 | 0.262 | 0.312 | 0.436 | 0.472 | 0.396 | 0.357 | 0.213 | 0.169 | 0.408 |
Q6_6 | 0.356 | 0.475 | 0.363 | 0.514 | 0.536 | 0.413 | 0.360 | 0.481 | 0.394 | 0.486 | 0.500 | 0.599 | 0.575 | 0.501 | 0.508 | 0.462 | 0.498 | 0.472 | 0.505 | 0.424 | 0.396 | 0.427 | 0.302 | 0.205 | 0.386 | 0.514 | 0.392 | 0.519 | 0.525 | 0.440 | 0.453 | 0.675 | 0.671 | 0.737 | 0.638 | 0.486 | 1.000 | 0.786 | 0.778 | 0.429 | 0.452 | 0.641 | 0.609 | 0.526 | 0.280 | 0.465 | 0.486 | 0.464 | 0.226 | 0.447 | 0.518 | 0.613 | 0.502 | 0.260 | 0.041 | 0.078 | 0.536 |
Q6_7 | 0.434 | 0.468 | 0.432 | 0.465 | 0.501 | 0.417 | 0.338 | 0.556 | 0.474 | 0.540 | 0.520 | 0.610 | 0.574 | 0.567 | 0.557 | 0.513 | 0.525 | 0.566 | 0.541 | 0.432 | 0.403 | 0.424 | 0.227 | 0.180 | 0.464 | 0.590 | 0.399 | 0.550 | 0.462 | 0.461 | 0.460 | 0.671 | 0.669 | 0.767 | 0.664 | 0.498 | 0.786 | 1.000 | 0.814 | 0.468 | 0.501 | 0.640 | 0.589 | 0.520 | 0.347 | 0.439 | 0.502 | 0.461 | 0.311 | 0.441 | 0.506 | 0.572 | 0.485 | 0.298 | 0.062 | 0.141 | 0.515 |
Q6_8 | 0.370 | 0.359 | 0.357 | 0.416 | 0.451 | 0.369 | 0.343 | 0.461 | 0.384 | 0.418 | 0.510 | 0.600 | 0.521 | 0.518 | 0.507 | 0.447 | 0.469 | 0.454 | 0.466 | 0.352 | 0.377 | 0.410 | 0.210 | 0.140 | 0.408 | 0.533 | 0.399 | 0.510 | 0.458 | 0.422 | 0.402 | 0.666 | 0.707 | 0.664 | 0.719 | 0.466 | 0.778 | 0.814 | 1.000 | 0.469 | 0.465 | 0.568 | 0.544 | 0.469 | 0.278 | 0.488 | 0.487 | 0.482 | 0.215 | 0.387 | 0.498 | 0.538 | 0.477 | 0.274 | 0.048 | 0.110 | 0.516 |
Q6_9 | 0.288 | 0.318 | 0.290 | 0.345 | 0.338 | 0.313 | 0.279 | 0.361 | 0.375 | 0.378 | 0.437 | 0.467 | 0.445 | 0.508 | 0.432 | 0.325 | 0.344 | 0.390 | 0.449 | 0.418 | 0.300 | 0.365 | 0.223 | 0.153 | 0.289 | 0.467 | 0.291 | 0.421 | 0.328 | 0.380 | 0.314 | 0.352 | 0.298 | 0.295 | 0.226 | 0.386 | 0.429 | 0.468 | 0.469 | 1.000 | 0.539 | 0.534 | 0.454 | 0.422 | 0.394 | 0.323 | 0.496 | 0.507 | 0.402 | 0.416 | 0.394 | 0.402 | 0.371 | 0.430 | 0.389 | 0.275 | 0.400 |
Q6_10 | 0.345 | 0.410 | 0.319 | 0.399 | 0.419 | 0.432 | 0.376 | 0.399 | 0.308 | 0.334 | 0.413 | 0.392 | 0.315 | 0.486 | 0.435 | 0.408 | 0.436 | 0.420 | 0.456 | 0.330 | 0.377 | 0.373 | 0.320 | 0.237 | 0.442 | 0.399 | 0.421 | 0.502 | 0.398 | 0.478 | 0.400 | 0.351 | 0.354 | 0.316 | 0.338 | 0.477 | 0.452 | 0.501 | 0.465 | 0.539 | 1.000 | 0.630 | 0.482 | 0.393 | 0.323 | 0.350 | 0.456 | 0.433 | 0.429 | 0.427 | 0.505 | 0.481 | 0.442 | 0.437 | 0.231 | 0.284 | 0.485 |
Q6_11 | 0.404 | 0.483 | 0.415 | 0.506 | 0.518 | 0.529 | 0.473 | 0.463 | 0.350 | 0.502 | 0.504 | 0.551 | 0.452 | 0.576 | 0.503 | 0.437 | 0.408 | 0.535 | 0.505 | 0.465 | 0.533 | 0.469 | 0.415 | 0.289 | 0.495 | 0.541 | 0.534 | 0.620 | 0.464 | 0.461 | 0.521 | 0.444 | 0.476 | 0.492 | 0.422 | 0.404 | 0.641 | 0.640 | 0.568 | 0.534 | 0.630 | 1.000 | 0.627 | 0.543 | 0.510 | 0.501 | 0.571 | 0.532 | 0.508 | 0.469 | 0.533 | 0.539 | 0.444 | 0.392 | 0.240 | 0.399 | 0.525 |
Q7_1 | 0.516 | 0.557 | 0.504 | 0.536 | 0.578 | 0.552 | 0.389 | 0.476 | 0.439 | 0.485 | 0.589 | 0.520 | 0.529 | 0.535 | 0.566 | 0.524 | 0.431 | 0.569 | 0.561 | 0.593 | 0.511 | 0.576 | 0.451 | 0.394 | 0.538 | 0.520 | 0.553 | 0.645 | 0.500 | 0.637 | 0.536 | 0.572 | 0.523 | 0.535 | 0.403 | 0.455 | 0.609 | 0.589 | 0.544 | 0.454 | 0.482 | 0.627 | 1.000 | 0.706 | 0.489 | 0.582 | 0.612 | 0.575 | 0.445 | 0.502 | 0.689 | 0.722 | 0.602 | 0.488 | 0.214 | 0.273 | 0.702 |
Q7_2 | 0.390 | 0.453 | 0.398 | 0.532 | 0.446 | 0.466 | 0.464 | 0.429 | 0.451 | 0.572 | 0.511 | 0.525 | 0.485 | 0.484 | 0.521 | 0.426 | 0.397 | 0.520 | 0.507 | 0.474 | 0.484 | 0.471 | 0.444 | 0.434 | 0.463 | 0.546 | 0.496 | 0.512 | 0.476 | 0.479 | 0.429 | 0.384 | 0.405 | 0.391 | 0.361 | 0.428 | 0.526 | 0.520 | 0.469 | 0.422 | 0.393 | 0.543 | 0.706 | 1.000 | 0.561 | 0.617 | 0.599 | 0.546 | 0.508 | 0.544 | 0.530 | 0.568 | 0.649 | 0.408 | 0.247 | 0.378 | 0.570 |
Q7_3 | 0.266 | 0.315 | 0.308 | 0.386 | 0.318 | 0.413 | 0.482 | 0.281 | 0.332 | 0.419 | 0.367 | 0.365 | 0.226 | 0.364 | 0.294 | 0.253 | 0.318 | 0.336 | 0.422 | 0.334 | 0.384 | 0.300 | 0.478 | 0.389 | 0.423 | 0.384 | 0.440 | 0.379 | 0.295 | 0.432 | 0.430 | 0.142 | 0.261 | 0.319 | 0.208 | 0.237 | 0.280 | 0.347 | 0.278 | 0.394 | 0.323 | 0.510 | 0.489 | 0.561 | 1.000 | 0.609 | 0.569 | 0.589 | 0.803 | 0.498 | 0.325 | 0.328 | 0.430 | 0.498 | 0.351 | 0.497 | 0.370 |
Q7_4 | 0.369 | 0.388 | 0.338 | 0.543 | 0.420 | 0.456 | 0.439 | 0.333 | 0.370 | 0.440 | 0.435 | 0.408 | 0.288 | 0.365 | 0.373 | 0.328 | 0.407 | 0.440 | 0.431 | 0.361 | 0.419 | 0.332 | 0.324 | 0.315 | 0.435 | 0.394 | 0.460 | 0.478 | 0.405 | 0.491 | 0.520 | 0.277 | 0.361 | 0.349 | 0.360 | 0.291 | 0.465 | 0.439 | 0.488 | 0.323 | 0.350 | 0.501 | 0.582 | 0.617 | 0.609 | 1.000 | 0.707 | 0.560 | 0.483 | 0.551 | 0.554 | 0.527 | 0.564 | 0.402 | 0.171 | 0.382 | 0.558 |
Q7_5 | 0.444 | 0.546 | 0.454 | 0.552 | 0.474 | 0.434 | 0.444 | 0.420 | 0.470 | 0.545 | 0.599 | 0.521 | 0.385 | 0.507 | 0.532 | 0.431 | 0.490 | 0.506 | 0.553 | 0.515 | 0.432 | 0.429 | 0.389 | 0.316 | 0.510 | 0.468 | 0.465 | 0.498 | 0.473 | 0.501 | 0.515 | 0.344 | 0.392 | 0.361 | 0.301 | 0.341 | 0.486 | 0.502 | 0.487 | 0.496 | 0.456 | 0.571 | 0.612 | 0.599 | 0.569 | 0.707 | 1.000 | 0.641 | 0.635 | 0.657 | 0.604 | 0.620 | 0.628 | 0.504 | 0.342 | 0.437 | 0.562 |
Q7_6 | 0.406 | 0.442 | 0.443 | 0.527 | 0.424 | 0.432 | 0.383 | 0.419 | 0.506 | 0.449 | 0.512 | 0.485 | 0.471 | 0.519 | 0.519 | 0.437 | 0.420 | 0.469 | 0.537 | 0.441 | 0.459 | 0.423 | 0.380 | 0.323 | 0.488 | 0.453 | 0.488 | 0.444 | 0.446 | 0.442 | 0.423 | 0.366 | 0.399 | 0.408 | 0.368 | 0.351 | 0.464 | 0.461 | 0.482 | 0.507 | 0.433 | 0.532 | 0.575 | 0.546 | 0.589 | 0.560 | 0.641 | 1.000 | 0.620 | 0.587 | 0.510 | 0.546 | 0.558 | 0.518 | 0.267 | 0.527 | 0.413 |
Q7_7 | 0.334 | 0.411 | 0.411 | 0.431 | 0.419 | 0.435 | 0.461 | 0.316 | 0.392 | 0.441 | 0.399 | 0.375 | 0.258 | 0.424 | 0.384 | 0.288 | 0.382 | 0.406 | 0.490 | 0.407 | 0.484 | 0.369 | 0.532 | 0.429 | 0.470 | 0.341 | 0.426 | 0.344 | 0.386 | 0.423 | 0.441 | 0.166 | 0.159 | 0.212 | 0.140 | 0.262 | 0.226 | 0.311 | 0.215 | 0.402 | 0.429 | 0.508 | 0.445 | 0.508 | 0.803 | 0.483 | 0.635 | 0.620 | 1.000 | 0.639 | 0.428 | 0.381 | 0.493 | 0.575 | 0.446 | 0.588 | 0.333 |
Q7_8 | 0.332 | 0.449 | 0.379 | 0.474 | 0.424 | 0.360 | 0.358 | 0.411 | 0.422 | 0.458 | 0.459 | 0.421 | 0.359 | 0.431 | 0.484 | 0.364 | 0.450 | 0.465 | 0.542 | 0.419 | 0.341 | 0.374 | 0.364 | 0.349 | 0.426 | 0.457 | 0.464 | 0.463 | 0.459 | 0.419 | 0.485 | 0.231 | 0.252 | 0.255 | 0.239 | 0.312 | 0.447 | 0.441 | 0.387 | 0.416 | 0.427 | 0.469 | 0.502 | 0.544 | 0.498 | 0.551 | 0.657 | 0.587 | 0.639 | 1.000 | 0.572 | 0.532 | 0.680 | 0.439 | 0.293 | 0.419 | 0.435 |
Q7_9 | 0.586 | 0.537 | 0.546 | 0.579 | 0.559 | 0.497 | 0.369 | 0.490 | 0.467 | 0.442 | 0.485 | 0.458 | 0.488 | 0.546 | 0.503 | 0.486 | 0.491 | 0.541 | 0.547 | 0.542 | 0.475 | 0.512 | 0.371 | 0.313 | 0.506 | 0.419 | 0.473 | 0.577 | 0.454 | 0.581 | 0.542 | 0.478 | 0.454 | 0.412 | 0.373 | 0.436 | 0.518 | 0.506 | 0.498 | 0.394 | 0.505 | 0.533 | 0.689 | 0.530 | 0.325 | 0.554 | 0.604 | 0.510 | 0.428 | 0.572 | 1.000 | 0.762 | 0.632 | 0.405 | 0.204 | 0.296 | 0.654 |
Q7_10 | 0.570 | 0.591 | 0.549 | 0.597 | 0.621 | 0.563 | 0.363 | 0.552 | 0.519 | 0.521 | 0.539 | 0.454 | 0.558 | 0.491 | 0.553 | 0.506 | 0.512 | 0.626 | 0.569 | 0.474 | 0.474 | 0.475 | 0.367 | 0.311 | 0.519 | 0.420 | 0.472 | 0.557 | 0.498 | 0.528 | 0.521 | 0.470 | 0.486 | 0.481 | 0.448 | 0.472 | 0.613 | 0.572 | 0.538 | 0.402 | 0.481 | 0.539 | 0.722 | 0.568 | 0.328 | 0.527 | 0.620 | 0.546 | 0.381 | 0.532 | 0.762 | 1.000 | 0.624 | 0.358 | 0.132 | 0.213 | 0.761 |
Q7_11 | 0.484 | 0.482 | 0.535 | 0.592 | 0.409 | 0.426 | 0.363 | 0.461 | 0.534 | 0.559 | 0.544 | 0.342 | 0.352 | 0.433 | 0.557 | 0.438 | 0.470 | 0.562 | 0.553 | 0.530 | 0.359 | 0.388 | 0.373 | 0.373 | 0.481 | 0.452 | 0.460 | 0.496 | 0.478 | 0.507 | 0.475 | 0.308 | 0.333 | 0.318 | 0.349 | 0.396 | 0.502 | 0.485 | 0.477 | 0.371 | 0.442 | 0.444 | 0.602 | 0.649 | 0.430 | 0.564 | 0.628 | 0.558 | 0.493 | 0.680 | 0.632 | 0.624 | 1.000 | 0.570 | 0.294 | 0.387 | 0.524 |
Q7_12 | 0.351 | 0.314 | 0.374 | 0.351 | 0.315 | 0.329 | 0.278 | 0.271 | 0.360 | 0.333 | 0.432 | 0.304 | 0.345 | 0.411 | 0.370 | 0.291 | 0.301 | 0.312 | 0.419 | 0.423 | 0.258 | 0.316 | 0.341 | 0.355 | 0.374 | 0.325 | 0.385 | 0.376 | 0.322 | 0.510 | 0.414 | 0.319 | 0.256 | 0.230 | 0.165 | 0.357 | 0.260 | 0.298 | 0.274 | 0.430 | 0.437 | 0.392 | 0.488 | 0.408 | 0.498 | 0.402 | 0.504 | 0.518 | 0.575 | 0.439 | 0.405 | 0.358 | 0.570 | 1.000 | 0.559 | 0.492 | 0.397 |
Q7_13 | 0.134 | 0.137 | 0.154 | 0.142 | 0.078 | 0.251 | 0.217 | 0.085 | 0.135 | 0.176 | 0.226 | 0.110 | 0.062 | 0.240 | 0.145 | 0.106 | 0.090 | 0.096 | 0.134 | 0.167 | 0.164 | 0.129 | 0.168 | 0.174 | 0.150 | 0.151 | 0.169 | 0.103 | 0.039 | 0.353 | 0.217 | 0.134 | 0.081 | 0.073 | 0.003 | 0.213 | 0.041 | 0.062 | 0.048 | 0.389 | 0.231 | 0.240 | 0.214 | 0.247 | 0.351 | 0.171 | 0.342 | 0.267 | 0.446 | 0.293 | 0.204 | 0.132 | 0.294 | 0.559 | 1.000 | 0.479 | 0.152 |
Q7_14 | 0.229 | 0.217 | 0.230 | 0.313 | 0.172 | 0.431 | 0.337 | 0.166 | 0.213 | 0.338 | 0.312 | 0.193 | 0.083 | 0.278 | 0.207 | 0.160 | 0.160 | 0.295 | 0.266 | 0.270 | 0.327 | 0.246 | 0.379 | 0.363 | 0.376 | 0.215 | 0.344 | 0.278 | 0.284 | 0.309 | 0.349 | 0.071 | 0.145 | 0.163 | 0.075 | 0.169 | 0.078 | 0.141 | 0.110 | 0.275 | 0.284 | 0.399 | 0.273 | 0.378 | 0.497 | 0.382 | 0.437 | 0.527 | 0.588 | 0.419 | 0.296 | 0.213 | 0.387 | 0.492 | 0.479 | 1.000 | 0.297 |
Q7_15 | 0.502 | 0.522 | 0.463 | 0.539 | 0.543 | 0.523 | 0.332 | 0.446 | 0.384 | 0.506 | 0.566 | 0.428 | 0.398 | 0.487 | 0.501 | 0.483 | 0.455 | 0.584 | 0.515 | 0.487 | 0.444 | 0.486 | 0.344 | 0.300 | 0.452 | 0.369 | 0.422 | 0.565 | 0.397 | 0.473 | 0.494 | 0.464 | 0.388 | 0.415 | 0.311 | 0.408 | 0.536 | 0.515 | 0.516 | 0.400 | 0.485 | 0.525 | 0.702 | 0.570 | 0.370 | 0.558 | 0.562 | 0.413 | 0.333 | 0.435 | 0.654 | 0.761 | 0.524 | 0.397 | 0.152 | 0.297 | 1.000 |
# Difference between correlation matrices
kable(corr.pc$rho-corr.ppm,digits=3,format = "html")%>%
kable_styling(full_width = T)%>%
scroll_box(width="100%", height="500px")
Q4_1 | Q4_2 | Q4_3 | Q4_4 | Q4_5 | Q4_6 | Q4_7 | Q4_8 | Q4_9 | Q4_10 | Q4_11 | Q4_12 | Q4_13 | Q4_14 | Q4_15 | Q4_16 | Q4_17 | Q4_18 | Q4_19 | Q5_1 | Q5_2 | Q5_3 | Q5_4 | Q5_5 | Q5_6 | Q5_7 | Q5_8 | Q5_9 | Q5_10 | Q5_11 | Q5_12 | Q6_1 | Q6_2 | Q6_3 | Q6_4 | Q6_5 | Q6_6 | Q6_7 | Q6_8 | Q6_9 | Q6_10 | Q6_11 | Q7_1 | Q7_2 | Q7_3 | Q7_4 | Q7_5 | Q7_6 | Q7_7 | Q7_8 | Q7_9 | Q7_10 | Q7_11 | Q7_12 | Q7_13 | Q7_14 | Q7_15 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Q4_1 | 0.000 | 0.072 | 0.076 | 0.080 | 0.066 | 0.049 | 0.032 | 0.070 | 0.060 | 0.075 | 0.062 | 0.063 | 0.092 | 0.064 | 0.069 | 0.066 | 0.065 | 0.079 | 0.063 | 0.052 | 0.040 | 0.045 | 0.031 | 0.036 | 0.044 | 0.042 | 0.028 | 0.055 | 0.054 | 0.052 | 0.034 | 0.077 | 0.050 | 0.069 | 0.050 | 0.050 | 0.066 | 0.065 | 0.057 | 0.042 | 0.036 | 0.047 | 0.058 | 0.050 | 0.019 | 0.038 | 0.046 | 0.049 | 0.047 | 0.034 | 0.058 | 0.075 | 0.061 | 0.044 | 0.007 | 0.011 | 0.057 |
Q4_2 | 0.072 | 0.000 | 0.076 | 0.081 | 0.073 | 0.065 | 0.039 | 0.072 | 0.062 | 0.077 | 0.069 | 0.069 | 0.097 | 0.050 | 0.071 | 0.064 | 0.067 | 0.074 | 0.063 | 0.066 | 0.053 | 0.059 | 0.049 | 0.046 | 0.065 | 0.043 | 0.054 | 0.066 | 0.076 | 0.060 | 0.053 | 0.086 | 0.057 | 0.066 | 0.042 | 0.060 | 0.084 | 0.076 | 0.058 | 0.052 | 0.046 | 0.061 | 0.074 | 0.066 | 0.030 | 0.046 | 0.072 | 0.058 | 0.059 | 0.055 | 0.066 | 0.086 | 0.075 | 0.034 | 0.008 | 0.020 | 0.069 |
Q4_3 | 0.076 | 0.076 | 0.000 | 0.086 | 0.060 | 0.049 | 0.020 | 0.074 | 0.071 | 0.079 | 0.060 | 0.058 | 0.082 | 0.043 | 0.063 | 0.059 | 0.066 | 0.072 | 0.063 | 0.054 | 0.040 | 0.044 | 0.026 | 0.035 | 0.059 | 0.040 | 0.038 | 0.056 | 0.050 | 0.058 | 0.030 | 0.090 | 0.043 | 0.069 | 0.041 | 0.065 | 0.061 | 0.065 | 0.047 | 0.045 | 0.035 | 0.046 | 0.055 | 0.042 | 0.018 | 0.036 | 0.048 | 0.053 | 0.034 | 0.042 | 0.058 | 0.069 | 0.064 | 0.029 | 0.006 | 0.019 | 0.052 |
Q4_4 | 0.080 | 0.081 | 0.086 | 0.000 | 0.072 | 0.055 | 0.039 | 0.081 | 0.074 | 0.090 | 0.068 | 0.083 | 0.085 | 0.048 | 0.064 | 0.066 | 0.084 | 0.086 | 0.064 | 0.056 | 0.033 | 0.051 | 0.031 | 0.034 | 0.049 | 0.040 | 0.035 | 0.056 | 0.052 | 0.049 | 0.044 | 0.071 | 0.059 | 0.085 | 0.047 | 0.065 | 0.106 | 0.071 | 0.062 | 0.055 | 0.035 | 0.045 | 0.067 | 0.057 | 0.016 | 0.056 | 0.053 | 0.054 | 0.028 | 0.038 | 0.058 | 0.081 | 0.075 | 0.017 | 0.008 | 0.006 | 0.062 |
Q4_5 | 0.066 | 0.073 | 0.060 | 0.072 | 0.000 | 0.059 | 0.039 | 0.058 | 0.045 | 0.075 | 0.062 | 0.072 | 0.109 | 0.060 | 0.066 | 0.062 | 0.065 | 0.068 | 0.065 | 0.057 | 0.052 | 0.052 | 0.059 | 0.048 | 0.054 | 0.048 | 0.054 | 0.066 | 0.072 | 0.058 | 0.058 | 0.073 | 0.057 | 0.074 | 0.052 | 0.052 | 0.080 | 0.076 | 0.062 | 0.050 | 0.051 | 0.058 | 0.068 | 0.060 | 0.038 | 0.053 | 0.055 | 0.057 | 0.051 | 0.053 | 0.068 | 0.071 | 0.061 | 0.033 | -0.007 | -0.001 | 0.069 |
Q4_6 | 0.049 | 0.065 | 0.049 | 0.055 | 0.059 | 0.000 | 0.070 | 0.056 | 0.042 | 0.061 | 0.047 | 0.053 | 0.079 | 0.045 | 0.050 | 0.054 | 0.052 | 0.066 | 0.054 | 0.040 | 0.044 | 0.046 | 0.037 | 0.033 | 0.044 | 0.040 | 0.036 | 0.052 | 0.036 | 0.042 | 0.040 | 0.060 | 0.055 | 0.060 | 0.038 | 0.034 | 0.063 | 0.054 | 0.045 | 0.037 | 0.045 | 0.043 | 0.056 | 0.051 | 0.032 | 0.038 | 0.034 | 0.038 | 0.065 | 0.033 | 0.049 | 0.065 | 0.050 | 0.029 | 0.026 | 0.031 | 0.057 |
Q4_7 | 0.032 | 0.039 | 0.020 | 0.039 | 0.039 | 0.070 | 0.000 | 0.024 | 0.019 | 0.030 | 0.045 | 0.049 | 0.026 | 0.047 | 0.033 | 0.046 | 0.041 | 0.033 | 0.037 | 0.036 | 0.024 | 0.030 | 0.020 | 0.009 | 0.043 | 0.065 | 0.034 | 0.049 | 0.042 | 0.041 | 0.035 | 0.048 | 0.050 | 0.053 | 0.045 | 0.024 | 0.065 | 0.043 | 0.057 | 0.040 | 0.039 | 0.045 | 0.047 | 0.050 | 0.030 | 0.039 | 0.035 | 0.025 | 0.035 | 0.018 | 0.035 | 0.051 | 0.041 | 0.012 | 0.018 | 0.002 | 0.048 |
Q4_8 | 0.070 | 0.072 | 0.074 | 0.081 | 0.058 | 0.056 | 0.024 | 0.000 | 0.057 | 0.081 | 0.062 | 0.067 | 0.097 | 0.060 | 0.064 | 0.059 | 0.068 | 0.077 | 0.073 | 0.050 | 0.047 | 0.052 | 0.030 | 0.030 | 0.048 | 0.043 | 0.048 | 0.053 | 0.057 | 0.046 | 0.045 | 0.069 | 0.046 | 0.073 | 0.045 | 0.052 | 0.071 | 0.067 | 0.054 | 0.051 | 0.046 | 0.057 | 0.061 | 0.059 | 0.028 | 0.037 | 0.049 | 0.055 | 0.047 | 0.052 | 0.056 | 0.064 | 0.064 | 0.025 | 0.003 | 0.010 | 0.049 |
Q4_9 | 0.060 | 0.062 | 0.071 | 0.074 | 0.045 | 0.042 | 0.019 | 0.057 | 0.000 | 0.073 | 0.053 | 0.053 | 0.092 | 0.051 | 0.064 | 0.054 | 0.055 | 0.066 | 0.060 | 0.051 | 0.044 | 0.042 | 0.031 | 0.042 | 0.048 | 0.046 | 0.038 | 0.051 | 0.053 | 0.051 | 0.051 | 0.078 | 0.037 | 0.079 | 0.039 | 0.056 | 0.062 | 0.063 | 0.052 | 0.044 | 0.028 | 0.042 | 0.060 | 0.069 | 0.031 | 0.044 | 0.057 | 0.056 | 0.046 | 0.048 | 0.058 | 0.061 | 0.071 | 0.040 | 0.006 | 0.015 | 0.044 |
Q4_10 | 0.075 | 0.077 | 0.079 | 0.090 | 0.075 | 0.061 | 0.030 | 0.081 | 0.073 | 0.000 | 0.072 | 0.096 | 0.114 | 0.055 | 0.081 | 0.076 | 0.081 | 0.103 | 0.087 | 0.066 | 0.025 | 0.062 | 0.044 | 0.043 | 0.055 | 0.053 | 0.051 | 0.069 | 0.066 | 0.060 | 0.053 | 0.083 | 0.071 | 0.103 | 0.067 | 0.074 | 0.103 | 0.106 | 0.082 | 0.067 | 0.047 | 0.060 | 0.066 | 0.075 | 0.042 | 0.048 | 0.059 | 0.058 | 0.046 | 0.050 | 0.057 | 0.089 | 0.075 | 0.024 | 0.018 | 0.021 | 0.066 |
Q4_11 | 0.062 | 0.069 | 0.060 | 0.068 | 0.062 | 0.047 | 0.045 | 0.062 | 0.053 | 0.072 | 0.000 | 0.077 | 0.114 | 0.055 | 0.061 | 0.060 | 0.065 | 0.074 | 0.060 | 0.052 | 0.041 | 0.048 | 0.037 | 0.036 | 0.045 | 0.051 | 0.043 | 0.057 | 0.064 | 0.054 | 0.041 | 0.077 | 0.053 | 0.072 | 0.047 | 0.058 | 0.072 | 0.071 | 0.068 | 0.054 | 0.039 | 0.054 | 0.063 | 0.064 | 0.033 | 0.043 | 0.057 | 0.059 | 0.051 | 0.045 | 0.049 | 0.058 | 0.074 | 0.046 | 0.022 | 0.020 | 0.058 |
Q4_12 | 0.063 | 0.069 | 0.058 | 0.083 | 0.072 | 0.053 | 0.049 | 0.067 | 0.053 | 0.096 | 0.077 | 0.000 | 0.121 | 0.085 | 0.064 | 0.071 | 0.063 | 0.081 | 0.062 | 0.059 | 0.054 | 0.051 | 0.053 | 0.041 | 0.056 | 0.069 | 0.054 | 0.068 | 0.083 | 0.051 | 0.054 | 0.092 | 0.068 | 0.094 | 0.058 | 0.079 | 0.099 | 0.083 | 0.086 | 0.066 | 0.057 | 0.074 | 0.070 | 0.084 | 0.063 | 0.051 | 0.070 | 0.057 | 0.064 | 0.053 | 0.060 | 0.057 | 0.067 | 0.046 | 0.007 | 0.013 | 0.058 |
Q4_13 | 0.092 | 0.097 | 0.082 | 0.085 | 0.109 | 0.079 | 0.026 | 0.097 | 0.092 | 0.114 | 0.114 | 0.121 | 0.000 | 0.133 | 0.086 | 0.092 | 0.067 | 0.118 | 0.118 | 0.115 | 0.109 | 0.099 | 0.042 | 0.032 | 0.082 | 0.092 | 0.083 | 0.099 | 0.110 | 0.085 | 0.093 | 0.121 | 0.098 | 0.102 | 0.092 | 0.116 | 0.099 | 0.130 | 0.096 | 0.116 | 0.059 | 0.095 | 0.116 | 0.114 | 0.056 | 0.064 | 0.104 | 0.114 | 0.056 | 0.076 | 0.100 | 0.103 | 0.094 | 0.079 | -0.012 | -0.013 | 0.083 |
Q4_14 | 0.064 | 0.050 | 0.043 | 0.048 | 0.060 | 0.045 | 0.047 | 0.060 | 0.051 | 0.055 | 0.055 | 0.085 | 0.133 | 0.000 | 0.071 | 0.069 | 0.058 | 0.067 | 0.059 | 0.055 | 0.040 | 0.058 | 0.034 | 0.025 | 0.049 | 0.046 | 0.043 | 0.058 | 0.049 | 0.059 | 0.032 | 0.102 | 0.071 | 0.086 | 0.063 | 0.066 | 0.079 | 0.086 | 0.081 | 0.066 | 0.058 | 0.047 | 0.058 | 0.047 | 0.028 | 0.033 | 0.046 | 0.057 | 0.053 | 0.033 | 0.055 | 0.070 | 0.053 | 0.051 | 0.022 | 0.006 | 0.060 |
Q4_15 | 0.069 | 0.071 | 0.063 | 0.064 | 0.066 | 0.050 | 0.033 | 0.064 | 0.064 | 0.081 | 0.061 | 0.064 | 0.086 | 0.071 | 0.000 | 0.073 | 0.064 | 0.079 | 0.066 | 0.053 | 0.046 | 0.059 | 0.053 | 0.037 | 0.065 | 0.056 | 0.052 | 0.063 | 0.065 | 0.051 | 0.050 | 0.066 | 0.060 | 0.079 | 0.051 | 0.054 | 0.078 | 0.077 | 0.063 | 0.051 | 0.045 | 0.053 | 0.063 | 0.066 | 0.029 | 0.041 | 0.059 | 0.068 | 0.052 | 0.055 | 0.056 | 0.061 | 0.071 | 0.044 | 0.008 | 0.007 | 0.054 |
Q4_16 | 0.066 | 0.064 | 0.059 | 0.066 | 0.062 | 0.054 | 0.046 | 0.059 | 0.054 | 0.076 | 0.060 | 0.071 | 0.092 | 0.069 | 0.073 | 0.000 | 0.072 | 0.073 | 0.063 | 0.049 | 0.040 | 0.059 | 0.038 | 0.031 | 0.066 | 0.053 | 0.045 | 0.062 | 0.060 | 0.053 | 0.047 | 0.095 | 0.071 | 0.084 | 0.061 | 0.043 | 0.085 | 0.072 | 0.066 | 0.050 | 0.048 | 0.049 | 0.057 | 0.054 | 0.017 | 0.037 | 0.048 | 0.052 | 0.028 | 0.035 | 0.054 | 0.066 | 0.053 | 0.036 | 0.004 | -0.004 | 0.060 |
Q4_17 | 0.065 | 0.067 | 0.066 | 0.084 | 0.065 | 0.052 | 0.041 | 0.068 | 0.055 | 0.081 | 0.065 | 0.063 | 0.067 | 0.058 | 0.064 | 0.072 | 0.000 | 0.076 | 0.066 | 0.057 | 0.053 | 0.048 | 0.034 | 0.026 | 0.054 | 0.054 | 0.045 | 0.055 | 0.070 | 0.051 | 0.046 | 0.073 | 0.041 | 0.075 | 0.050 | 0.039 | 0.077 | 0.070 | 0.056 | 0.048 | 0.057 | 0.048 | 0.055 | 0.056 | 0.037 | 0.047 | 0.058 | 0.054 | 0.049 | 0.055 | 0.060 | 0.060 | 0.067 | 0.029 | -0.007 | 0.011 | 0.056 |
Q4_18 | 0.079 | 0.074 | 0.072 | 0.086 | 0.068 | 0.066 | 0.033 | 0.077 | 0.066 | 0.103 | 0.074 | 0.081 | 0.118 | 0.067 | 0.079 | 0.073 | 0.076 | 0.000 | 0.072 | 0.067 | 0.058 | 0.060 | 0.046 | 0.051 | 0.069 | 0.058 | 0.061 | 0.075 | 0.088 | 0.054 | 0.054 | 0.084 | 0.052 | 0.084 | 0.049 | 0.051 | 0.084 | 0.082 | 0.061 | 0.058 | 0.053 | 0.064 | 0.073 | 0.071 | 0.031 | 0.054 | 0.060 | 0.057 | 0.054 | 0.050 | 0.062 | 0.076 | 0.092 | 0.040 | 0.000 | 0.024 | 0.072 |
Q4_19 | 0.063 | 0.063 | 0.063 | 0.064 | 0.065 | 0.054 | 0.037 | 0.073 | 0.060 | 0.087 | 0.060 | 0.062 | 0.118 | 0.059 | 0.066 | 0.063 | 0.066 | 0.072 | 0.000 | 0.058 | 0.049 | 0.051 | 0.032 | 0.031 | 0.053 | 0.057 | 0.044 | 0.065 | 0.061 | 0.051 | 0.049 | 0.095 | 0.055 | 0.091 | 0.060 | 0.060 | 0.083 | 0.079 | 0.064 | 0.062 | 0.049 | 0.053 | 0.066 | 0.054 | 0.046 | 0.044 | 0.050 | 0.054 | 0.061 | 0.063 | 0.061 | 0.061 | 0.074 | 0.050 | 0.004 | 0.018 | 0.057 |
Q5_1 | 0.052 | 0.066 | 0.054 | 0.056 | 0.057 | 0.040 | 0.036 | 0.050 | 0.051 | 0.066 | 0.052 | 0.059 | 0.115 | 0.055 | 0.053 | 0.049 | 0.057 | 0.067 | 0.058 | 0.000 | 0.044 | 0.057 | 0.047 | 0.036 | 0.056 | 0.044 | 0.051 | 0.057 | 0.066 | 0.054 | 0.052 | 0.078 | 0.038 | 0.049 | 0.027 | 0.062 | 0.075 | 0.052 | 0.048 | 0.056 | 0.028 | 0.048 | 0.057 | 0.049 | 0.024 | 0.033 | 0.047 | 0.042 | 0.043 | 0.034 | 0.051 | 0.051 | 0.069 | 0.041 | 0.011 | 0.014 | 0.052 |
Q5_2 | 0.040 | 0.053 | 0.040 | 0.033 | 0.052 | 0.044 | 0.024 | 0.047 | 0.044 | 0.025 | 0.041 | 0.054 | 0.109 | 0.040 | 0.046 | 0.040 | 0.053 | 0.058 | 0.049 | 0.044 | 0.000 | 0.057 | 0.021 | 0.016 | 0.049 | 0.034 | 0.030 | 0.046 | 0.036 | 0.037 | 0.031 | 0.073 | 0.044 | 0.067 | 0.046 | 0.053 | 0.070 | 0.054 | 0.054 | 0.042 | 0.026 | 0.039 | 0.039 | 0.027 | 0.001 | 0.022 | 0.029 | 0.029 | 0.042 | 0.014 | 0.039 | 0.057 | 0.024 | 0.004 | 0.010 | 0.000 | 0.041 |
Q5_3 | 0.045 | 0.059 | 0.044 | 0.051 | 0.052 | 0.046 | 0.030 | 0.052 | 0.042 | 0.062 | 0.048 | 0.051 | 0.099 | 0.058 | 0.059 | 0.059 | 0.048 | 0.060 | 0.051 | 0.057 | 0.057 | 0.000 | 0.052 | 0.043 | 0.061 | 0.044 | 0.053 | 0.056 | 0.057 | 0.051 | 0.047 | 0.086 | 0.049 | 0.058 | 0.041 | 0.043 | 0.065 | 0.053 | 0.055 | 0.051 | 0.038 | 0.046 | 0.056 | 0.055 | 0.020 | 0.033 | 0.042 | 0.046 | 0.044 | 0.040 | 0.050 | 0.054 | 0.048 | 0.023 | 0.007 | 0.004 | 0.051 |
Q5_4 | 0.031 | 0.049 | 0.026 | 0.031 | 0.059 | 0.037 | 0.020 | 0.030 | 0.031 | 0.044 | 0.037 | 0.053 | 0.042 | 0.034 | 0.053 | 0.038 | 0.034 | 0.046 | 0.032 | 0.047 | 0.021 | 0.052 | 0.000 | 0.056 | 0.046 | 0.019 | 0.047 | 0.055 | 0.037 | 0.062 | 0.046 | 0.021 | 0.021 | 0.037 | 0.007 | 0.032 | 0.034 | 0.017 | 0.019 | 0.049 | 0.022 | 0.028 | 0.037 | 0.023 | 0.040 | 0.017 | 0.026 | 0.034 | 0.063 | 0.051 | 0.026 | 0.045 | 0.017 | 0.032 | 0.023 | 0.009 | 0.034 |
Q5_5 | 0.036 | 0.046 | 0.035 | 0.034 | 0.048 | 0.033 | 0.009 | 0.030 | 0.042 | 0.043 | 0.036 | 0.041 | 0.032 | 0.025 | 0.037 | 0.031 | 0.026 | 0.051 | 0.031 | 0.036 | 0.016 | 0.043 | 0.056 | 0.000 | 0.041 | 0.014 | 0.043 | 0.051 | 0.037 | 0.060 | 0.045 | 0.025 | 0.032 | 0.036 | 0.015 | 0.040 | 0.020 | 0.021 | 0.021 | 0.043 | 0.012 | 0.017 | 0.039 | 0.022 | 0.030 | 0.011 | 0.015 | 0.031 | 0.039 | 0.034 | 0.029 | 0.050 | 0.008 | 0.022 | 0.024 | 0.015 | 0.034 |
Q5_6 | 0.044 | 0.065 | 0.059 | 0.049 | 0.054 | 0.044 | 0.043 | 0.048 | 0.048 | 0.055 | 0.045 | 0.056 | 0.082 | 0.049 | 0.065 | 0.066 | 0.054 | 0.069 | 0.053 | 0.056 | 0.049 | 0.061 | 0.046 | 0.041 | 0.000 | 0.031 | 0.049 | 0.060 | 0.029 | 0.061 | 0.048 | 0.057 | 0.048 | 0.063 | 0.037 | 0.057 | 0.053 | 0.056 | 0.057 | 0.039 | 0.045 | 0.034 | 0.050 | 0.019 | 0.022 | 0.028 | 0.039 | 0.043 | 0.048 | 0.032 | 0.051 | 0.066 | 0.055 | 0.026 | 0.011 | 0.004 | 0.048 |
Q5_7 | 0.042 | 0.043 | 0.040 | 0.040 | 0.048 | 0.040 | 0.065 | 0.043 | 0.046 | 0.053 | 0.051 | 0.069 | 0.092 | 0.046 | 0.056 | 0.053 | 0.054 | 0.058 | 0.057 | 0.044 | 0.034 | 0.044 | 0.019 | 0.014 | 0.031 | 0.000 | 0.035 | 0.056 | 0.051 | 0.049 | 0.030 | 0.083 | 0.062 | 0.084 | 0.051 | 0.057 | 0.072 | 0.080 | 0.073 | 0.062 | 0.043 | 0.050 | 0.055 | 0.049 | 0.043 | 0.034 | 0.037 | 0.038 | 0.030 | 0.028 | 0.050 | 0.048 | 0.049 | 0.027 | 0.016 | 0.004 | 0.038 |
Q5_8 | 0.028 | 0.054 | 0.038 | 0.035 | 0.054 | 0.036 | 0.034 | 0.048 | 0.038 | 0.051 | 0.043 | 0.054 | 0.083 | 0.043 | 0.052 | 0.045 | 0.045 | 0.061 | 0.044 | 0.051 | 0.030 | 0.053 | 0.047 | 0.043 | 0.049 | 0.035 | 0.000 | 0.056 | 0.050 | 0.051 | 0.036 | 0.058 | 0.043 | 0.062 | 0.032 | 0.063 | 0.057 | 0.041 | 0.048 | 0.040 | 0.039 | 0.038 | 0.047 | 0.037 | 0.024 | 0.034 | 0.028 | 0.044 | 0.039 | 0.041 | 0.040 | 0.050 | 0.039 | 0.025 | 0.017 | 0.021 | 0.042 |
Q5_9 | 0.055 | 0.066 | 0.056 | 0.056 | 0.066 | 0.052 | 0.049 | 0.053 | 0.051 | 0.069 | 0.057 | 0.068 | 0.099 | 0.058 | 0.063 | 0.062 | 0.055 | 0.075 | 0.065 | 0.057 | 0.046 | 0.056 | 0.055 | 0.051 | 0.060 | 0.056 | 0.056 | 0.000 | 0.074 | 0.054 | 0.049 | 0.088 | 0.062 | 0.069 | 0.050 | 0.059 | 0.071 | 0.067 | 0.063 | 0.058 | 0.053 | 0.056 | 0.058 | 0.051 | 0.032 | 0.043 | 0.047 | 0.045 | 0.036 | 0.042 | 0.056 | 0.056 | 0.064 | 0.034 | 0.000 | 0.014 | 0.059 |
Q5_10 | 0.054 | 0.076 | 0.050 | 0.052 | 0.072 | 0.036 | 0.042 | 0.057 | 0.053 | 0.066 | 0.064 | 0.083 | 0.110 | 0.049 | 0.065 | 0.060 | 0.070 | 0.088 | 0.061 | 0.066 | 0.036 | 0.057 | 0.037 | 0.037 | 0.029 | 0.051 | 0.050 | 0.074 | 0.000 | 0.072 | 0.035 | 0.081 | 0.057 | 0.090 | 0.050 | 0.061 | 0.105 | 0.078 | 0.070 | 0.067 | 0.034 | 0.034 | 0.064 | 0.050 | 0.005 | 0.042 | 0.051 | 0.050 | 0.051 | 0.042 | 0.055 | 0.081 | 0.063 | 0.024 | -0.001 | 0.004 | 0.054 |
Q5_11 | 0.052 | 0.060 | 0.058 | 0.049 | 0.058 | 0.042 | 0.041 | 0.046 | 0.051 | 0.060 | 0.054 | 0.051 | 0.085 | 0.059 | 0.051 | 0.053 | 0.051 | 0.054 | 0.051 | 0.054 | 0.037 | 0.051 | 0.062 | 0.060 | 0.061 | 0.049 | 0.051 | 0.054 | 0.072 | 0.000 | 0.054 | 0.083 | 0.052 | 0.049 | 0.029 | 0.055 | 0.064 | 0.055 | 0.052 | 0.042 | 0.056 | 0.047 | 0.061 | 0.046 | 0.049 | 0.046 | 0.046 | 0.049 | 0.069 | 0.048 | 0.055 | 0.056 | 0.057 | 0.056 | 0.036 | 0.030 | 0.050 |
Q5_12 | 0.034 | 0.053 | 0.030 | 0.044 | 0.058 | 0.040 | 0.035 | 0.045 | 0.051 | 0.053 | 0.041 | 0.054 | 0.093 | 0.032 | 0.050 | 0.047 | 0.046 | 0.054 | 0.049 | 0.052 | 0.031 | 0.047 | 0.046 | 0.045 | 0.048 | 0.030 | 0.036 | 0.049 | 0.035 | 0.054 | 0.000 | 0.067 | 0.060 | 0.063 | 0.040 | 0.046 | 0.075 | 0.055 | 0.056 | 0.049 | 0.028 | 0.039 | 0.055 | 0.031 | 0.018 | 0.036 | 0.033 | 0.027 | 0.031 | 0.032 | 0.056 | 0.065 | 0.043 | 0.017 | 0.017 | -0.005 | 0.048 |
Q6_1 | 0.077 | 0.086 | 0.090 | 0.071 | 0.073 | 0.060 | 0.048 | 0.069 | 0.078 | 0.083 | 0.077 | 0.092 | 0.121 | 0.102 | 0.066 | 0.095 | 0.073 | 0.084 | 0.095 | 0.078 | 0.073 | 0.086 | 0.021 | 0.025 | 0.057 | 0.083 | 0.058 | 0.088 | 0.081 | 0.083 | 0.067 | 0.000 | 0.093 | 0.102 | 0.090 | 0.095 | 0.098 | 0.113 | 0.100 | 0.072 | 0.066 | 0.075 | 0.100 | 0.084 | 0.025 | 0.057 | 0.066 | 0.077 | 0.024 | 0.046 | 0.100 | 0.081 | 0.071 | 0.063 | 0.010 | -0.009 | 0.100 |
Q6_2 | 0.050 | 0.057 | 0.043 | 0.059 | 0.057 | 0.055 | 0.050 | 0.046 | 0.037 | 0.071 | 0.053 | 0.068 | 0.098 | 0.071 | 0.060 | 0.071 | 0.041 | 0.052 | 0.055 | 0.038 | 0.044 | 0.049 | 0.021 | 0.032 | 0.048 | 0.062 | 0.043 | 0.062 | 0.057 | 0.052 | 0.060 | 0.093 | 0.000 | 0.078 | 0.064 | 0.082 | 0.077 | 0.076 | 0.076 | 0.046 | 0.042 | 0.058 | 0.062 | 0.061 | 0.024 | 0.038 | 0.048 | 0.046 | 0.007 | 0.034 | 0.054 | 0.051 | 0.046 | 0.013 | -0.013 | -0.005 | 0.044 |
Q6_3 | 0.069 | 0.066 | 0.069 | 0.085 | 0.074 | 0.060 | 0.053 | 0.073 | 0.079 | 0.103 | 0.072 | 0.094 | 0.102 | 0.086 | 0.079 | 0.084 | 0.075 | 0.084 | 0.091 | 0.049 | 0.067 | 0.058 | 0.037 | 0.036 | 0.063 | 0.084 | 0.062 | 0.069 | 0.090 | 0.049 | 0.063 | 0.102 | 0.078 | 0.000 | 0.091 | 0.087 | 0.098 | 0.099 | 0.090 | 0.069 | 0.047 | 0.077 | 0.088 | 0.079 | 0.048 | 0.054 | 0.067 | 0.075 | 0.033 | 0.041 | 0.076 | 0.077 | 0.070 | 0.013 | -0.022 | -0.001 | 0.069 |
Q6_4 | 0.050 | 0.042 | 0.041 | 0.047 | 0.052 | 0.038 | 0.045 | 0.045 | 0.039 | 0.067 | 0.047 | 0.058 | 0.092 | 0.063 | 0.051 | 0.061 | 0.050 | 0.049 | 0.060 | 0.027 | 0.046 | 0.041 | 0.007 | 0.015 | 0.037 | 0.051 | 0.032 | 0.050 | 0.050 | 0.029 | 0.040 | 0.090 | 0.064 | 0.091 | 0.000 | 0.060 | 0.078 | 0.073 | 0.079 | 0.035 | 0.039 | 0.055 | 0.047 | 0.046 | 0.019 | 0.040 | 0.036 | 0.039 | -0.002 | 0.022 | 0.045 | 0.054 | 0.045 | 0.003 | -0.019 | -0.021 | 0.033 |
Q6_5 | 0.050 | 0.060 | 0.065 | 0.065 | 0.052 | 0.034 | 0.024 | 0.052 | 0.056 | 0.074 | 0.058 | 0.079 | 0.116 | 0.066 | 0.054 | 0.043 | 0.039 | 0.051 | 0.060 | 0.062 | 0.053 | 0.043 | 0.032 | 0.040 | 0.057 | 0.057 | 0.063 | 0.059 | 0.061 | 0.055 | 0.046 | 0.095 | 0.082 | 0.087 | 0.060 | 0.000 | 0.081 | 0.063 | 0.070 | 0.057 | 0.055 | 0.055 | 0.078 | 0.074 | 0.027 | 0.049 | 0.046 | 0.055 | 0.028 | 0.038 | 0.064 | 0.063 | 0.059 | 0.035 | 0.002 | 0.016 | 0.063 |
Q6_6 | 0.066 | 0.084 | 0.061 | 0.106 | 0.080 | 0.063 | 0.065 | 0.071 | 0.062 | 0.103 | 0.072 | 0.099 | 0.099 | 0.079 | 0.078 | 0.085 | 0.077 | 0.084 | 0.083 | 0.075 | 0.070 | 0.065 | 0.034 | 0.020 | 0.053 | 0.072 | 0.057 | 0.071 | 0.105 | 0.064 | 0.075 | 0.098 | 0.077 | 0.098 | 0.078 | 0.081 | 0.000 | 0.105 | 0.088 | 0.083 | 0.056 | 0.108 | 0.090 | 0.086 | 0.030 | 0.075 | 0.080 | 0.077 | 0.017 | 0.065 | 0.077 | 0.079 | 0.089 | 0.025 | -0.019 | -0.027 | 0.091 |
Q6_7 | 0.065 | 0.076 | 0.065 | 0.071 | 0.076 | 0.054 | 0.043 | 0.067 | 0.063 | 0.106 | 0.071 | 0.083 | 0.130 | 0.086 | 0.077 | 0.072 | 0.070 | 0.082 | 0.079 | 0.052 | 0.054 | 0.053 | 0.017 | 0.021 | 0.056 | 0.080 | 0.041 | 0.067 | 0.078 | 0.055 | 0.055 | 0.113 | 0.076 | 0.099 | 0.073 | 0.063 | 0.105 | 0.000 | 0.086 | 0.067 | 0.057 | 0.082 | 0.075 | 0.070 | 0.046 | 0.055 | 0.065 | 0.052 | 0.037 | 0.047 | 0.059 | 0.069 | 0.070 | 0.027 | -0.013 | -0.011 | 0.071 |
Q6_8 | 0.057 | 0.058 | 0.047 | 0.062 | 0.062 | 0.045 | 0.057 | 0.054 | 0.052 | 0.082 | 0.068 | 0.086 | 0.096 | 0.081 | 0.063 | 0.066 | 0.056 | 0.061 | 0.064 | 0.048 | 0.054 | 0.055 | 0.019 | 0.021 | 0.057 | 0.073 | 0.048 | 0.063 | 0.070 | 0.052 | 0.056 | 0.100 | 0.076 | 0.090 | 0.079 | 0.070 | 0.088 | 0.086 | 0.000 | 0.066 | 0.049 | 0.069 | 0.067 | 0.068 | 0.043 | 0.064 | 0.063 | 0.060 | 0.018 | 0.040 | 0.062 | 0.052 | 0.072 | 0.024 | -0.008 | 0.002 | 0.059 |
Q6_9 | 0.042 | 0.052 | 0.045 | 0.055 | 0.050 | 0.037 | 0.040 | 0.051 | 0.044 | 0.067 | 0.054 | 0.066 | 0.116 | 0.066 | 0.051 | 0.050 | 0.048 | 0.058 | 0.062 | 0.056 | 0.042 | 0.051 | 0.049 | 0.043 | 0.039 | 0.062 | 0.040 | 0.058 | 0.067 | 0.042 | 0.049 | 0.072 | 0.046 | 0.069 | 0.035 | 0.057 | 0.083 | 0.067 | 0.066 | 0.000 | 0.067 | 0.065 | 0.067 | 0.066 | 0.055 | 0.050 | 0.064 | 0.056 | 0.068 | 0.052 | 0.059 | 0.059 | 0.066 | 0.071 | 0.038 | 0.036 | 0.063 |
Q6_10 | 0.036 | 0.046 | 0.035 | 0.035 | 0.051 | 0.045 | 0.039 | 0.046 | 0.028 | 0.047 | 0.039 | 0.057 | 0.059 | 0.058 | 0.045 | 0.048 | 0.057 | 0.053 | 0.049 | 0.028 | 0.026 | 0.038 | 0.022 | 0.012 | 0.045 | 0.043 | 0.039 | 0.053 | 0.034 | 0.056 | 0.028 | 0.066 | 0.042 | 0.047 | 0.039 | 0.055 | 0.056 | 0.057 | 0.049 | 0.067 | 0.000 | 0.053 | 0.051 | 0.015 | 0.023 | 0.025 | 0.034 | 0.030 | 0.069 | 0.037 | 0.049 | 0.062 | 0.045 | 0.049 | 0.033 | 0.021 | 0.057 |
Q6_11 | 0.047 | 0.061 | 0.046 | 0.045 | 0.058 | 0.043 | 0.045 | 0.057 | 0.042 | 0.060 | 0.054 | 0.074 | 0.095 | 0.047 | 0.053 | 0.049 | 0.048 | 0.064 | 0.053 | 0.048 | 0.039 | 0.046 | 0.028 | 0.017 | 0.034 | 0.050 | 0.038 | 0.056 | 0.034 | 0.047 | 0.039 | 0.075 | 0.058 | 0.077 | 0.055 | 0.055 | 0.108 | 0.082 | 0.069 | 0.065 | 0.053 | 0.000 | 0.059 | 0.038 | 0.024 | 0.030 | 0.047 | 0.039 | 0.039 | 0.028 | 0.048 | 0.062 | 0.048 | 0.026 | 0.023 | 0.021 | 0.058 |
Q7_1 | 0.058 | 0.074 | 0.055 | 0.067 | 0.068 | 0.056 | 0.047 | 0.061 | 0.060 | 0.066 | 0.063 | 0.070 | 0.116 | 0.058 | 0.063 | 0.057 | 0.055 | 0.073 | 0.066 | 0.057 | 0.039 | 0.056 | 0.037 | 0.039 | 0.050 | 0.055 | 0.047 | 0.058 | 0.064 | 0.061 | 0.055 | 0.100 | 0.062 | 0.088 | 0.047 | 0.078 | 0.090 | 0.075 | 0.067 | 0.067 | 0.051 | 0.059 | 0.000 | 0.069 | 0.042 | 0.052 | 0.054 | 0.054 | 0.038 | 0.048 | 0.057 | 0.081 | 0.069 | 0.041 | 0.019 | 0.003 | 0.070 |
Q7_2 | 0.050 | 0.066 | 0.042 | 0.057 | 0.060 | 0.051 | 0.050 | 0.059 | 0.069 | 0.075 | 0.064 | 0.084 | 0.114 | 0.047 | 0.066 | 0.054 | 0.056 | 0.071 | 0.054 | 0.049 | 0.027 | 0.055 | 0.023 | 0.022 | 0.019 | 0.049 | 0.037 | 0.051 | 0.050 | 0.046 | 0.031 | 0.084 | 0.061 | 0.079 | 0.046 | 0.074 | 0.086 | 0.070 | 0.068 | 0.066 | 0.015 | 0.038 | 0.069 | 0.000 | 0.058 | 0.045 | 0.033 | 0.029 | 0.044 | 0.030 | 0.047 | 0.075 | 0.045 | 0.030 | 0.029 | 0.010 | 0.068 |
Q7_3 | 0.019 | 0.030 | 0.018 | 0.016 | 0.038 | 0.032 | 0.030 | 0.028 | 0.031 | 0.042 | 0.033 | 0.063 | 0.056 | 0.028 | 0.029 | 0.017 | 0.037 | 0.031 | 0.046 | 0.024 | 0.001 | 0.020 | 0.040 | 0.030 | 0.022 | 0.043 | 0.024 | 0.032 | 0.005 | 0.049 | 0.018 | 0.025 | 0.024 | 0.048 | 0.019 | 0.027 | 0.030 | 0.046 | 0.043 | 0.055 | 0.023 | 0.024 | 0.042 | 0.058 | 0.000 | 0.044 | 0.025 | 0.049 | 0.071 | 0.033 | 0.017 | 0.039 | 0.020 | 0.041 | 0.027 | 0.012 | 0.036 |
Q7_4 | 0.038 | 0.046 | 0.036 | 0.056 | 0.053 | 0.038 | 0.039 | 0.037 | 0.044 | 0.048 | 0.043 | 0.051 | 0.064 | 0.033 | 0.041 | 0.037 | 0.047 | 0.054 | 0.044 | 0.033 | 0.022 | 0.033 | 0.017 | 0.011 | 0.028 | 0.034 | 0.034 | 0.043 | 0.042 | 0.046 | 0.036 | 0.057 | 0.038 | 0.054 | 0.040 | 0.049 | 0.075 | 0.055 | 0.064 | 0.050 | 0.025 | 0.030 | 0.052 | 0.045 | 0.044 | 0.000 | 0.037 | 0.036 | 0.037 | 0.044 | 0.046 | 0.063 | 0.052 | 0.029 | 0.016 | 0.022 | 0.053 |
Q7_5 | 0.046 | 0.072 | 0.048 | 0.053 | 0.055 | 0.034 | 0.035 | 0.049 | 0.057 | 0.059 | 0.057 | 0.070 | 0.104 | 0.046 | 0.059 | 0.048 | 0.058 | 0.060 | 0.050 | 0.047 | 0.029 | 0.042 | 0.026 | 0.015 | 0.039 | 0.037 | 0.028 | 0.047 | 0.051 | 0.046 | 0.033 | 0.066 | 0.048 | 0.067 | 0.036 | 0.046 | 0.080 | 0.065 | 0.063 | 0.064 | 0.034 | 0.047 | 0.054 | 0.033 | 0.025 | 0.037 | 0.000 | 0.044 | 0.067 | 0.053 | 0.048 | 0.065 | 0.050 | 0.037 | 0.043 | 0.025 | 0.056 |
Q7_6 | 0.049 | 0.058 | 0.053 | 0.054 | 0.057 | 0.038 | 0.025 | 0.055 | 0.056 | 0.058 | 0.059 | 0.057 | 0.114 | 0.057 | 0.068 | 0.052 | 0.054 | 0.057 | 0.054 | 0.042 | 0.029 | 0.046 | 0.034 | 0.031 | 0.043 | 0.038 | 0.044 | 0.045 | 0.050 | 0.049 | 0.027 | 0.077 | 0.046 | 0.075 | 0.039 | 0.055 | 0.077 | 0.052 | 0.060 | 0.056 | 0.030 | 0.039 | 0.054 | 0.029 | 0.049 | 0.036 | 0.044 | 0.000 | 0.058 | 0.042 | 0.043 | 0.071 | 0.050 | 0.045 | 0.033 | 0.040 | 0.045 |
Q7_7 | 0.047 | 0.059 | 0.034 | 0.028 | 0.051 | 0.065 | 0.035 | 0.047 | 0.046 | 0.046 | 0.051 | 0.064 | 0.056 | 0.053 | 0.052 | 0.028 | 0.049 | 0.054 | 0.061 | 0.043 | 0.042 | 0.044 | 0.063 | 0.039 | 0.048 | 0.030 | 0.039 | 0.036 | 0.051 | 0.069 | 0.031 | 0.024 | 0.007 | 0.033 | -0.002 | 0.028 | 0.017 | 0.037 | 0.018 | 0.068 | 0.069 | 0.039 | 0.038 | 0.044 | 0.071 | 0.037 | 0.067 | 0.058 | 0.000 | 0.042 | 0.043 | 0.049 | 0.034 | 0.072 | 0.068 | 0.057 | 0.046 |
Q7_8 | 0.034 | 0.055 | 0.042 | 0.038 | 0.053 | 0.033 | 0.018 | 0.052 | 0.048 | 0.050 | 0.045 | 0.053 | 0.076 | 0.033 | 0.055 | 0.035 | 0.055 | 0.050 | 0.063 | 0.034 | 0.014 | 0.040 | 0.051 | 0.034 | 0.032 | 0.028 | 0.041 | 0.042 | 0.042 | 0.048 | 0.032 | 0.046 | 0.034 | 0.041 | 0.022 | 0.038 | 0.065 | 0.047 | 0.040 | 0.052 | 0.037 | 0.028 | 0.048 | 0.030 | 0.033 | 0.044 | 0.053 | 0.042 | 0.042 | 0.000 | 0.057 | 0.067 | 0.059 | 0.048 | 0.038 | 0.026 | 0.046 |
Q7_9 | 0.058 | 0.066 | 0.058 | 0.058 | 0.068 | 0.049 | 0.035 | 0.056 | 0.058 | 0.057 | 0.049 | 0.060 | 0.100 | 0.055 | 0.056 | 0.054 | 0.060 | 0.062 | 0.061 | 0.051 | 0.039 | 0.050 | 0.026 | 0.029 | 0.051 | 0.050 | 0.040 | 0.056 | 0.055 | 0.055 | 0.056 | 0.100 | 0.054 | 0.076 | 0.045 | 0.064 | 0.077 | 0.059 | 0.062 | 0.059 | 0.049 | 0.048 | 0.057 | 0.047 | 0.017 | 0.046 | 0.048 | 0.043 | 0.043 | 0.057 | 0.000 | 0.069 | 0.065 | 0.031 | 0.017 | 0.019 | 0.061 |
Q7_10 | 0.075 | 0.086 | 0.069 | 0.081 | 0.071 | 0.065 | 0.051 | 0.064 | 0.061 | 0.089 | 0.058 | 0.057 | 0.103 | 0.070 | 0.061 | 0.066 | 0.060 | 0.076 | 0.061 | 0.051 | 0.057 | 0.054 | 0.045 | 0.050 | 0.066 | 0.048 | 0.050 | 0.056 | 0.081 | 0.056 | 0.065 | 0.081 | 0.051 | 0.077 | 0.054 | 0.063 | 0.079 | 0.069 | 0.052 | 0.059 | 0.062 | 0.062 | 0.081 | 0.075 | 0.039 | 0.063 | 0.065 | 0.071 | 0.049 | 0.067 | 0.069 | 0.000 | 0.086 | 0.035 | 0.006 | 0.023 | 0.081 |
Q7_11 | 0.061 | 0.075 | 0.064 | 0.075 | 0.061 | 0.050 | 0.041 | 0.064 | 0.071 | 0.075 | 0.074 | 0.067 | 0.094 | 0.053 | 0.071 | 0.053 | 0.067 | 0.092 | 0.074 | 0.069 | 0.024 | 0.048 | 0.017 | 0.008 | 0.055 | 0.049 | 0.039 | 0.064 | 0.063 | 0.057 | 0.043 | 0.071 | 0.046 | 0.070 | 0.045 | 0.059 | 0.089 | 0.070 | 0.072 | 0.066 | 0.045 | 0.048 | 0.069 | 0.045 | 0.020 | 0.052 | 0.050 | 0.050 | 0.034 | 0.059 | 0.065 | 0.086 | 0.000 | 0.051 | 0.034 | 0.042 | 0.079 |
Q7_12 | 0.044 | 0.034 | 0.029 | 0.017 | 0.033 | 0.029 | 0.012 | 0.025 | 0.040 | 0.024 | 0.046 | 0.046 | 0.079 | 0.051 | 0.044 | 0.036 | 0.029 | 0.040 | 0.050 | 0.041 | 0.004 | 0.023 | 0.032 | 0.022 | 0.026 | 0.027 | 0.025 | 0.034 | 0.024 | 0.056 | 0.017 | 0.063 | 0.013 | 0.013 | 0.003 | 0.035 | 0.025 | 0.027 | 0.024 | 0.071 | 0.049 | 0.026 | 0.041 | 0.030 | 0.041 | 0.029 | 0.037 | 0.045 | 0.072 | 0.048 | 0.031 | 0.035 | 0.051 | 0.000 | 0.076 | 0.044 | 0.031 |
Q7_13 | 0.007 | 0.008 | 0.006 | 0.008 | -0.007 | 0.026 | 0.018 | 0.003 | 0.006 | 0.018 | 0.022 | 0.007 | -0.012 | 0.022 | 0.008 | 0.004 | -0.007 | 0.000 | 0.004 | 0.011 | 0.010 | 0.007 | 0.023 | 0.024 | 0.011 | 0.016 | 0.017 | 0.000 | -0.001 | 0.036 | 0.017 | 0.010 | -0.013 | -0.022 | -0.019 | 0.002 | -0.019 | -0.013 | -0.008 | 0.038 | 0.033 | 0.023 | 0.019 | 0.029 | 0.027 | 0.016 | 0.043 | 0.033 | 0.068 | 0.038 | 0.017 | 0.006 | 0.034 | 0.076 | 0.000 | 0.055 | 0.014 |
Q7_14 | 0.011 | 0.020 | 0.019 | 0.006 | -0.001 | 0.031 | 0.002 | 0.010 | 0.015 | 0.021 | 0.020 | 0.013 | -0.013 | 0.006 | 0.007 | -0.004 | 0.011 | 0.024 | 0.018 | 0.014 | 0.000 | 0.004 | 0.009 | 0.015 | 0.004 | 0.004 | 0.021 | 0.014 | 0.004 | 0.030 | -0.005 | -0.009 | -0.005 | -0.001 | -0.021 | 0.016 | -0.027 | -0.011 | 0.002 | 0.036 | 0.021 | 0.021 | 0.003 | 0.010 | 0.012 | 0.022 | 0.025 | 0.040 | 0.057 | 0.026 | 0.019 | 0.023 | 0.042 | 0.044 | 0.055 | 0.000 | 0.012 |
Q7_15 | 0.057 | 0.069 | 0.052 | 0.062 | 0.069 | 0.057 | 0.048 | 0.049 | 0.044 | 0.066 | 0.058 | 0.058 | 0.083 | 0.060 | 0.054 | 0.060 | 0.056 | 0.072 | 0.057 | 0.052 | 0.041 | 0.051 | 0.034 | 0.034 | 0.048 | 0.038 | 0.042 | 0.059 | 0.054 | 0.050 | 0.048 | 0.100 | 0.044 | 0.069 | 0.033 | 0.063 | 0.091 | 0.071 | 0.059 | 0.063 | 0.057 | 0.058 | 0.070 | 0.068 | 0.036 | 0.053 | 0.056 | 0.045 | 0.046 | 0.046 | 0.061 | 0.081 | 0.079 | 0.031 | 0.014 | 0.012 | 0.000 |
# What % of PC correlations are higher than PPM?
a <- sum(round(corr.pc$rho - corr.ppm, 3) > 0)/2
b <- sum(round(corr.pc$rho - corr.ppm, 3) < 0)/2
prop.diff <- a/(a+b)
prop.diff
[1] 0.9868173
# Is this difference significantly different than .5?
X <- table(c(rep(0,a),rep(1,b)))
prop.test(x=X, alternative = 'greater')
1-sample proportions test with continuity correction
data: X, null probability 0.5
X-squared = 1508.2, df = 1, p-value < 2.2e-16
alternative hypothesis: true p is greater than 0.5
95 percent confidence interval:
0.9808562 1.0000000
sample estimates:
p
0.9868173
evalues<-eigen(corr.pc$rho)$values
evalues
[1] 2.627313e+01 3.761010e+00 2.952063e+00 2.210781e+00 1.460550e+00
[6] 1.397493e+00 1.274058e+00 1.101728e+00 1.011097e+00 9.481728e-01
[11] 8.631385e-01 7.519192e-01 7.257157e-01 7.148329e-01 6.489492e-01
[16] 6.317037e-01 6.070564e-01 5.773193e-01 5.627900e-01 5.426212e-01
[21] 5.001011e-01 4.759799e-01 4.542633e-01 4.423228e-01 4.201005e-01
[26] 4.067098e-01 3.823340e-01 3.695824e-01 3.251477e-01 3.064071e-01
[31] 2.924240e-01 2.856197e-01 2.675262e-01 2.658989e-01 2.568959e-01
[36] 2.417409e-01 2.170894e-01 2.100147e-01 1.954760e-01 1.827397e-01
[41] 1.693641e-01 1.613067e-01 1.502327e-01 1.461206e-01 1.426707e-01
[46] 1.223941e-01 1.080088e-01 9.494902e-02 8.224543e-02 7.330500e-02
[51] 6.150090e-02 5.520100e-02 4.169916e-02 3.892286e-02 2.619869e-02
[56] 1.138168e-02 9.990371e-11
plotnScree(nScree(evalues, model="factors"), main="Scree Plot & Parallel Analysis")
psych::fa.parallel(dat,main="Parallel Analysis",
fm = "pa",cor = "cov")
Parallel analysis suggests that the number of factors = 6 and the number of components = 4
psych::fa.parallel(corr.pc$rho,main="Parallel Analysis",
n.obs = nrow(mydata), fm = "pa", cor = "cov")
Warning in fa.stats(r = r, f = f, phi = phi, n.obs = n.obs, np.obs = np.obs, :
The estimated weights for the factor scores are probably incorrect. Try a
different factor score estimation method.
Parallel analysis suggests that the number of factors = 7 and the number of components = 4
Note that the warning for the “estimated weights for the factor scores…” is not particularly impacting because we do not intend to obtain factor scores.
fit <- psych::fa(r = corr.pc$rho, nfactors = 3, rotate = "Promax", fm = "pa")
Warning in fa.stats(r = r, f = f, phi = phi, n.obs = n.obs, np.obs = np.obs, :
The estimated weights for the factor scores are probably incorrect. Try a
different factor score estimation method.
fit
Factor Analysis using method = pa
Call: psych::fa(r = corr.pc$rho, nfactors = 3, rotate = "Promax", fm = "pa")
Standardized loadings (pattern matrix) based upon correlation matrix
PA1 PA2 PA3 h2 u2 com
Q4_1 1.00 -0.07 -0.20 0.66 0.34 1.1
Q4_2 0.99 -0.03 -0.17 0.72 0.28 1.1
Q4_3 0.98 -0.01 -0.24 0.66 0.34 1.1
Q4_4 0.85 0.14 -0.19 0.69 0.31 1.2
Q4_5 0.68 0.02 0.09 0.58 0.42 1.0
Q4_6 0.29 0.38 0.08 0.47 0.53 2.0
Q4_7 0.04 0.54 0.03 0.35 0.65 1.0
Q4_8 0.97 -0.20 -0.02 0.68 0.32 1.1
Q4_9 0.74 0.03 -0.07 0.50 0.50 1.0
Q4_10 0.74 0.13 -0.09 0.60 0.40 1.1
Q4_11 0.72 0.10 0.01 0.65 0.35 1.0
Q4_12 0.43 -0.05 0.41 0.56 0.44 2.0
Q4_13 0.60 -0.25 0.41 0.59 0.41 2.2
Q4_14 0.48 0.12 0.21 0.55 0.45 1.5
Q4_15 0.77 0.00 0.06 0.67 0.33 1.0
Q4_16 0.66 -0.05 0.15 0.56 0.44 1.1
Q4_17 0.75 -0.09 0.08 0.55 0.45 1.1
Q4_18 1.04 -0.06 -0.12 0.83 0.17 1.0
Q4_19 0.73 0.11 0.00 0.67 0.33 1.0
Q5_1 0.38 0.36 0.00 0.48 0.52 2.0
Q5_2 0.07 0.48 0.17 0.44 0.56 1.3
Q5_3 0.21 0.36 0.17 0.45 0.55 2.1
Q5_4 0.00 0.75 -0.15 0.44 0.56 1.1
Q5_5 0.02 0.72 -0.22 0.37 0.63 1.2
Q5_6 0.16 0.58 0.03 0.54 0.46 1.2
Q5_7 -0.05 0.35 0.45 0.48 0.52 1.9
Q5_8 -0.01 0.63 0.13 0.52 0.48 1.1
Q5_9 0.21 0.34 0.30 0.59 0.41 2.6
Q5_10 0.21 0.30 0.21 0.43 0.57 2.6
Q5_11 0.22 0.44 0.11 0.50 0.50 1.6
Q5_12 0.04 0.54 0.17 0.49 0.51 1.2
Q6_1 -0.06 -0.21 0.98 0.67 0.33 1.1
Q6_2 -0.21 -0.10 1.05 0.72 0.28 1.1
Q6_3 -0.19 -0.10 1.03 0.72 0.28 1.1
Q6_4 -0.18 -0.17 1.00 0.61 0.39 1.1
Q6_5 0.03 0.16 0.42 0.32 0.68 1.3
Q6_6 0.01 -0.09 0.91 0.74 0.26 1.0
Q6_7 0.08 -0.10 0.88 0.76 0.24 1.0
Q6_8 -0.08 -0.09 0.98 0.74 0.26 1.0
Q6_9 0.02 0.37 0.24 0.33 0.67 1.7
Q6_10 0.02 0.39 0.26 0.39 0.61 1.7
Q6_11 -0.04 0.47 0.40 0.59 0.41 2.0
Q7_1 0.11 0.43 0.35 0.66 0.34 2.1
Q7_2 0.04 0.58 0.18 0.56 0.44 1.2
Q7_3 -0.24 0.98 -0.11 0.57 0.43 1.2
Q7_4 -0.07 0.65 0.14 0.48 0.52 1.1
Q7_5 0.11 0.67 0.04 0.61 0.39 1.1
Q7_6 0.04 0.63 0.11 0.54 0.46 1.1
Q7_7 -0.05 1.05 -0.35 0.68 0.32 1.2
Q7_8 0.10 0.67 -0.06 0.50 0.50 1.1
Q7_9 0.29 0.33 0.20 0.55 0.45 2.6
Q7_10 0.38 0.19 0.28 0.60 0.40 2.4
Q7_11 0.25 0.54 -0.02 0.54 0.46 1.4
Q7_12 -0.06 0.76 -0.10 0.43 0.57 1.0
Q7_13 -0.23 0.72 -0.20 0.24 0.76 1.4
Q7_14 -0.21 0.97 -0.31 0.46 0.54 1.3
Q7_15 0.28 0.28 0.22 0.50 0.50 2.9
PA1 PA2 PA3
SS loadings 11.98 11.37 8.44
Proportion Var 0.21 0.20 0.15
Cumulative Var 0.21 0.41 0.56
Proportion Explained 0.38 0.36 0.27
Cumulative Proportion 0.38 0.73 1.00
With factor correlations of
PA1 PA2 PA3
PA1 1.00 0.74 0.73
PA2 0.74 1.00 0.68
PA3 0.73 0.68 1.00
Mean item complexity = 1.4
Test of the hypothesis that 3 factors are sufficient.
The degrees of freedom for the null model are 1596 and the objective function was 84.54
The degrees of freedom for the model are 1428 and the objective function was 44.36
The root mean square of the residuals (RMSR) is 0.05
The df corrected root mean square of the residuals is 0.06
Fit based upon off diagonal values = 0.99
print(fit$loadings, cutoff=0.3)
Loadings:
PA1 PA2 PA3
Q4_1 0.997
Q4_2 0.990
Q4_3 0.982
Q4_4 0.854
Q4_5 0.680
Q4_6 0.380
Q4_7 0.543
Q4_8 0.970
Q4_9 0.737
Q4_10 0.739
Q4_11 0.721
Q4_12 0.431 0.411
Q4_13 0.595 0.415
Q4_14 0.476
Q4_15 0.770
Q4_16 0.664
Q4_17 0.747
Q4_18 1.039
Q4_19 0.727
Q5_1 0.379 0.361
Q5_2 0.479
Q5_3 0.365
Q5_4 0.754
Q5_5 0.724
Q5_6 0.583
Q5_7 0.349 0.446
Q5_8 0.635
Q5_9 0.342 0.302
Q5_10 0.304
Q5_11 0.440
Q5_12 0.539
Q6_1 0.985
Q6_2 1.050
Q6_3 1.033
Q6_4 1.000
Q6_5 0.415
Q6_6 0.914
Q6_7 0.880
Q6_8 0.979
Q6_9 0.369
Q6_10 0.395
Q6_11 0.473 0.395
Q7_1 0.431 0.350
Q7_2 0.581
Q7_3 0.981
Q7_4 0.648
Q7_5 0.673
Q7_6 0.632
Q7_7 1.051 -0.349
Q7_8 0.670
Q7_9 0.335
Q7_10 0.381
Q7_11 0.540
Q7_12 0.762
Q7_13 0.721
Q7_14 0.969 -0.312
Q7_15
PA1 PA2 PA3
SS loadings 11.797 11.310 8.941
Proportion Var 0.207 0.198 0.157
Cumulative Var 0.207 0.405 0.562
fit <- psych::fa(r = cov.dat, nfactors = 3, rotate = "Promax", fm = "pa", covar = T)
fit
Factor Analysis using method = pa
Call: psych::fa(r = cov.dat, nfactors = 3, rotate = "Promax", covar = T,
fm = "pa")
Unstandardized loadings (pattern matrix) based upon covariance matrix
PA2 PA1 PA3 h2 u2 H2 U2
Q4_1 -0.05 0.80 -0.17 0.42 0.33 0.57 0.43
Q4_2 -0.05 0.78 -0.15 0.43 0.25 0.63 0.37
Q4_3 0.00 0.76 -0.20 0.40 0.30 0.57 0.43
Q4_4 0.14 0.63 -0.16 0.39 0.27 0.59 0.41
Q4_5 -0.01 0.60 0.06 0.40 0.37 0.52 0.48
Q4_6 0.35 0.27 0.08 0.41 0.56 0.42 0.58
Q4_7 0.50 0.06 -0.01 0.29 0.59 0.33 0.67
Q4_8 -0.20 0.87 -0.03 0.52 0.34 0.61 0.39
Q4_9 -0.02 0.76 -0.09 0.47 0.54 0.46 0.54
Q4_10 0.11 0.55 -0.11 0.31 0.31 0.50 0.50
Q4_11 0.05 0.71 -0.01 0.55 0.37 0.60 0.40
Q4_12 -0.11 0.51 0.36 0.54 0.57 0.49 0.51
Q4_13 -0.25 0.54 0.29 0.36 0.41 0.47 0.53
Q4_14 0.09 0.47 0.13 0.40 0.40 0.50 0.50
Q4_15 -0.04 0.72 0.03 0.52 0.32 0.62 0.38
Q4_16 -0.03 0.62 0.09 0.44 0.45 0.49 0.51
Q4_17 -0.13 0.73 0.06 0.46 0.47 0.49 0.51
Q4_18 -0.07 0.83 -0.11 0.50 0.18 0.73 0.27
Q4_19 0.06 0.75 -0.04 0.58 0.36 0.62 0.38
Q5_1 0.32 0.35 -0.01 0.39 0.51 0.43 0.57
Q5_2 0.54 0.06 0.13 0.46 0.61 0.43 0.57
Q5_3 0.38 0.22 0.15 0.46 0.64 0.42 0.58
Q5_4 0.85 -0.06 -0.13 0.53 0.69 0.44 0.56
Q5_5 0.79 -0.06 -0.20 0.41 0.66 0.38 0.62
Q5_6 0.56 0.10 0.02 0.42 0.40 0.52 0.48
Q5_7 0.32 -0.01 0.37 0.38 0.50 0.43 0.57
Q5_8 0.67 -0.02 0.13 0.55 0.56 0.50 0.50
Q5_9 0.33 0.21 0.28 0.53 0.46 0.53 0.47
Q5_10 0.27 0.16 0.13 0.26 0.44 0.37 0.63
Q5_11 0.34 0.24 0.11 0.40 0.50 0.44 0.56
Q5_12 0.51 0.05 0.14 0.41 0.49 0.46 0.54
Q6_1 -0.17 -0.04 0.75 0.39 0.32 0.55 0.45
Q6_2 -0.08 -0.16 0.89 0.55 0.28 0.66 0.34
Q6_3 -0.07 -0.18 0.88 0.53 0.33 0.62 0.38
Q6_4 -0.12 -0.13 0.84 0.46 0.40 0.54 0.46
Q6_5 0.13 0.06 0.37 0.27 0.80 0.25 0.75
Q6_6 -0.09 0.03 0.69 0.43 0.24 0.64 0.36
Q6_7 -0.10 0.10 0.71 0.51 0.25 0.67 0.33
Q6_8 -0.12 0.00 0.82 0.54 0.27 0.67 0.33
Q6_9 0.30 0.14 0.25 0.39 1.10 0.26 0.74
Q6_10 0.30 0.07 0.23 0.29 0.54 0.35 0.65
Q6_11 0.44 0.00 0.34 0.51 0.43 0.54 0.46
Q7_1 0.35 0.13 0.29 0.48 0.33 0.59 0.41
Q7_2 0.49 0.05 0.12 0.37 0.36 0.51 0.49
Q7_3 0.92 -0.20 -0.10 0.54 0.49 0.53 0.47
Q7_4 0.58 -0.03 0.13 0.42 0.54 0.44 0.56
Q7_5 0.57 0.14 0.03 0.50 0.40 0.55 0.45
Q7_6 0.53 0.06 0.09 0.41 0.43 0.49 0.51
Q7_7 0.94 -0.03 -0.27 0.59 0.44 0.57 0.43
Q7_8 0.52 0.12 -0.04 0.34 0.43 0.44 0.56
Q7_9 0.29 0.31 0.18 0.49 0.50 0.50 0.50
Q7_10 0.12 0.37 0.26 0.47 0.43 0.52 0.48
Q7_11 0.42 0.20 -0.02 0.33 0.38 0.47 0.53
Q7_12 0.67 -0.02 -0.05 0.39 0.66 0.37 0.63
Q7_13 0.56 -0.16 -0.11 0.17 0.81 0.17 0.83
Q7_14 0.87 -0.19 -0.21 0.40 0.57 0.42 0.58
Q7_15 0.21 0.28 0.18 0.36 0.46 0.44 0.56
PA2 PA1 PA3
SS loadings 9.48 9.40 5.85
Proportion Var 0.19 0.19 0.12
Cumulative Var 0.19 0.37 0.49
Proportion Explained 0.38 0.38 0.24
Cumulative Proportion 0.38 0.76 1.00
Standardized loadings (pattern matrix)
item PA2 PA1 PA3 h2 u2
Q4_1 1 -0.05 0.92 -0.20 0.57 0.43
Q4_2 2 -0.06 0.96 -0.18 0.63 0.37
Q4_3 3 0.00 0.91 -0.24 0.57 0.43
Q4_4 4 0.17 0.78 -0.20 0.59 0.41
Q4_5 5 -0.01 0.68 0.07 0.52 0.48
Q4_6 6 0.36 0.27 0.08 0.42 0.58
Q4_7 7 0.53 0.06 -0.01 0.33 0.67
Q4_8 8 -0.21 0.94 -0.03 0.61 0.39
Q4_9 9 -0.02 0.76 -0.09 0.46 0.54
Q4_10 10 0.14 0.69 -0.13 0.50 0.50
Q4_11 11 0.05 0.75 -0.01 0.60 0.40
Q4_12 12 -0.11 0.49 0.35 0.49 0.51
Q4_13 13 -0.29 0.61 0.33 0.47 0.53
Q4_14 14 0.10 0.52 0.14 0.50 0.50
Q4_15 15 -0.04 0.79 0.04 0.62 0.38
Q4_16 16 -0.03 0.66 0.09 0.49 0.51
Q4_17 17 -0.13 0.75 0.06 0.49 0.51
Q4_18 18 -0.08 1.01 -0.13 0.73 0.27
Q4_19 19 0.06 0.77 -0.05 0.62 0.38
Q5_1 20 0.34 0.37 -0.01 0.43 0.57
Q5_2 21 0.52 0.06 0.12 0.43 0.57
Q5_3 22 0.37 0.21 0.14 0.42 0.58
Q5_4 23 0.76 -0.05 -0.11 0.44 0.56
Q5_5 24 0.77 -0.06 -0.19 0.38 0.62
Q5_6 25 0.62 0.11 0.02 0.52 0.48
Q5_7 26 0.34 -0.01 0.39 0.43 0.57
Q5_8 27 0.63 -0.02 0.12 0.50 0.50
Q5_9 28 0.33 0.21 0.28 0.53 0.47
Q5_10 29 0.32 0.19 0.16 0.37 0.63
Q5_11 30 0.36 0.26 0.12 0.44 0.56
Q5_12 31 0.53 0.05 0.14 0.46 0.54
Q6_1 32 -0.20 -0.05 0.89 0.55 0.45
Q6_2 33 -0.09 -0.18 0.98 0.66 0.34
Q6_3 34 -0.08 -0.19 0.95 0.62 0.38
Q6_4 35 -0.13 -0.14 0.90 0.54 0.46
Q6_5 36 0.13 0.06 0.36 0.25 0.75
Q6_6 37 -0.11 0.04 0.84 0.64 0.36
Q6_7 38 -0.11 0.11 0.81 0.67 0.33
Q6_8 39 -0.14 -0.01 0.90 0.67 0.33
Q6_9 40 0.25 0.12 0.21 0.26 0.74
Q6_10 41 0.33 0.07 0.26 0.35 0.65
Q6_11 42 0.45 0.00 0.35 0.54 0.46
Q7_1 43 0.39 0.14 0.32 0.59 0.41
Q7_2 44 0.57 0.05 0.14 0.51 0.49
Q7_3 45 0.91 -0.20 -0.10 0.53 0.47
Q7_4 46 0.59 -0.03 0.13 0.44 0.56
Q7_5 47 0.61 0.14 0.03 0.55 0.45
Q7_6 48 0.57 0.07 0.10 0.49 0.51
Q7_7 49 0.93 -0.03 -0.27 0.57 0.43
Q7_8 50 0.59 0.14 -0.04 0.44 0.56
Q7_9 51 0.29 0.32 0.18 0.50 0.50
Q7_10 52 0.12 0.40 0.28 0.52 0.48
Q7_11 53 0.50 0.24 -0.02 0.47 0.53
Q7_12 54 0.65 -0.02 -0.05 0.37 0.63
Q7_13 55 0.57 -0.16 -0.12 0.17 0.83
Q7_14 56 0.88 -0.20 -0.22 0.42 0.58
Q7_15 57 0.23 0.30 0.20 0.44 0.56
PA2 PA1 PA3
SS loadings 10.65 10.55 6.57
Proportion Var 0.19 0.19 0.12
Cumulative Var 0.19 0.37 0.49
Cum. factor Var 0.38 0.76 1.00
With factor correlations of
PA2 PA1 PA3
PA2 1.00 0.74 0.65
PA1 0.74 1.00 0.72
PA3 0.65 0.72 1.00
Mean item complexity = 1.4
Test of the hypothesis that 3 factors are sufficient.
The degrees of freedom for the null model are 1596 and the objective function was 46.33
The degrees of freedom for the model are 1428 and the objective function was 12.51
The root mean square of the residuals (RMSR) is 0.05
The df corrected root mean square of the residuals is 0.05
Fit based upon off diagonal values = 0.98
Measures of factor score adequacy
PA2 PA1 PA3
Correlation of (regression) scores with factors 0.98 0.98 0.98
Multiple R square of scores with factors 0.95 0.97 0.95
Minimum correlation of possible factor scores 0.90 0.93 0.90
print(fit$loadings, cutoff=0.3)
Loadings:
PA2 PA1 PA3
Q4_1 0.796
Q4_2 0.784
Q4_3 0.758
Q4_4 0.633
Q4_5 0.596
Q4_6 0.349
Q4_7 0.497
Q4_8 0.875
Q4_9 0.764
Q4_10 0.548
Q4_11 0.712
Q4_12 0.512 0.364
Q4_13 0.538
Q4_14 0.470
Q4_15 0.724
Q4_16 0.616
Q4_17 0.727
Q4_18 0.827
Q4_19 0.748
Q5_1 0.322 0.352
Q5_2 0.540
Q5_3 0.382
Q5_4 0.846
Q5_5 0.792
Q5_6 0.560
Q5_7 0.322 0.368
Q5_8 0.667
Q5_9 0.327
Q5_10
Q5_11 0.341
Q5_12 0.507
Q6_1 0.751
Q6_2 0.893
Q6_3 0.881
Q6_4 0.837
Q6_5 0.372
Q6_6 0.688
Q6_7 0.709
Q6_8 0.815
Q6_9 0.301
Q6_10 0.300
Q6_11 0.439 0.343
Q7_1 0.354
Q7_2 0.486
Q7_3 0.923
Q7_4 0.581
Q7_5 0.574
Q7_6 0.528
Q7_7 0.938
Q7_8 0.516
Q7_9 0.313
Q7_10 0.374
Q7_11 0.422
Q7_12 0.670
Q7_13 0.564
Q7_14 0.867
Q7_15
PA2 PA1 PA3
SS loadings 9.482 9.219 6.036
Proportion Var 0.166 0.162 0.106
Cumulative Var 0.166 0.328 0.434
fit <- psych::fa(r = corr.pc$rho, nfactors = 4, rotate = "Promax", fm = "pa")
Warning in fa.stats(r = r, f = f, phi = phi, n.obs = n.obs, np.obs = np.obs, :
The estimated weights for the factor scores are probably incorrect. Try a
different factor score estimation method.
fit
Factor Analysis using method = pa
Call: psych::fa(r = corr.pc$rho, nfactors = 4, rotate = "Promax", fm = "pa")
Standardized loadings (pattern matrix) based upon correlation matrix
PA1 PA3 PA2 PA4 h2 u2 com
Q4_1 0.99 -0.20 -0.09 0.02 0.66 0.34 1.1
Q4_2 0.99 -0.18 -0.06 0.04 0.72 0.28 1.1
Q4_3 0.98 -0.25 -0.02 0.01 0.66 0.34 1.1
Q4_4 0.86 -0.19 0.13 0.00 0.69 0.31 1.1
Q4_5 0.67 0.08 -0.09 0.14 0.59 0.41 1.2
Q4_6 0.27 0.06 0.15 0.30 0.48 0.52 2.6
Q4_7 0.03 0.02 0.33 0.28 0.35 0.65 2.0
Q4_8 0.98 -0.01 -0.13 -0.10 0.68 0.32 1.1
Q4_9 0.76 -0.06 0.13 -0.13 0.52 0.48 1.1
Q4_10 0.75 -0.09 0.15 -0.04 0.61 0.39 1.1
Q4_11 0.74 0.02 0.13 -0.05 0.66 0.34 1.1
Q4_12 0.44 0.42 0.03 -0.12 0.57 0.43 2.2
Q4_13 0.60 0.42 -0.17 -0.10 0.59 0.41 2.1
Q4_14 0.48 0.21 0.10 0.02 0.56 0.44 1.5
Q4_15 0.76 0.06 -0.06 0.08 0.67 0.33 1.0
Q4_16 0.64 0.13 -0.23 0.24 0.59 0.41 1.6
Q4_17 0.76 0.09 -0.01 -0.12 0.56 0.44 1.1
Q4_18 1.03 -0.13 -0.11 0.06 0.83 0.17 1.1
Q4_19 0.74 0.01 0.12 -0.02 0.67 0.33 1.1
Q5_1 0.35 -0.02 0.08 0.36 0.50 0.50 2.1
Q5_2 0.02 0.13 0.00 0.64 0.55 0.45 1.1
Q5_3 0.14 0.12 -0.15 0.69 0.61 0.39 1.2
Q5_4 -0.09 -0.23 0.10 0.93 0.67 0.33 1.2
Q5_5 -0.06 -0.30 0.09 0.90 0.59 0.41 1.3
Q5_6 0.09 -0.03 0.00 0.80 0.71 0.29 1.0
Q5_7 -0.07 0.43 0.11 0.30 0.49 0.51 2.0
Q5_8 -0.08 0.08 0.08 0.75 0.65 0.35 1.1
Q5_9 0.16 0.27 -0.05 0.52 0.66 0.34 1.8
Q5_10 0.19 0.19 0.03 0.35 0.45 0.55 2.1
Q5_11 0.21 0.10 0.25 0.24 0.50 0.50 3.3
Q5_12 0.01 0.15 0.21 0.43 0.51 0.49 1.8
Q6_1 -0.07 0.98 -0.19 -0.03 0.67 0.33 1.1
Q6_2 -0.22 1.05 -0.16 0.07 0.72 0.28 1.1
Q6_3 -0.20 1.03 -0.16 0.07 0.72 0.28 1.1
Q6_4 -0.18 1.00 -0.19 0.02 0.61 0.39 1.1
Q6_5 0.04 0.43 0.18 -0.04 0.32 0.68 1.4
Q6_6 0.02 0.93 -0.02 -0.11 0.75 0.25 1.0
Q6_7 0.09 0.90 0.02 -0.17 0.78 0.22 1.1
Q6_8 -0.07 1.00 0.03 -0.18 0.77 0.23 1.1
Q6_9 0.06 0.28 0.53 -0.23 0.41 0.59 1.9
Q6_10 0.04 0.28 0.37 0.02 0.40 0.60 1.9
Q6_11 -0.03 0.40 0.38 0.11 0.59 0.41 2.2
Q7_1 0.11 0.35 0.28 0.18 0.66 0.34 2.7
Q7_2 0.06 0.19 0.49 0.10 0.57 0.43 1.4
Q7_3 -0.22 -0.09 0.89 0.11 0.60 0.40 1.2
Q7_4 -0.04 0.16 0.63 0.01 0.51 0.49 1.1
Q7_5 0.14 0.07 0.74 -0.10 0.68 0.32 1.1
Q7_6 0.07 0.13 0.66 -0.05 0.59 0.41 1.1
Q7_7 -0.02 -0.33 0.96 0.12 0.72 0.28 1.3
Q7_8 0.13 -0.04 0.70 -0.05 0.55 0.45 1.1
Q7_9 0.30 0.20 0.27 0.07 0.56 0.44 2.9
Q7_10 0.39 0.28 0.17 0.02 0.60 0.40 2.3
Q7_11 0.28 0.00 0.57 -0.05 0.58 0.42 1.5
Q7_12 -0.03 -0.07 0.79 -0.04 0.49 0.51 1.0
Q7_13 -0.19 -0.17 0.82 -0.12 0.32 0.68 1.3
Q7_14 -0.19 -0.30 0.83 0.17 0.48 0.52 1.5
Q7_15 0.29 0.22 0.23 0.05 0.50 0.50 2.9
PA1 PA3 PA2 PA4
SS loadings 11.90 8.39 7.74 5.64
Proportion Var 0.21 0.15 0.14 0.10
Cumulative Var 0.21 0.36 0.49 0.59
Proportion Explained 0.35 0.25 0.23 0.17
Cumulative Proportion 0.35 0.60 0.83 1.00
With factor correlations of
PA1 PA3 PA2 PA4
PA1 1.00 0.74 0.70 0.67
PA3 0.74 1.00 0.64 0.63
PA2 0.70 0.64 1.00 0.68
PA4 0.67 0.63 0.68 1.00
Mean item complexity = 1.5
Test of the hypothesis that 4 factors are sufficient.
The degrees of freedom for the null model are 1596 and the objective function was 84.54
The degrees of freedom for the model are 1374 and the objective function was 42.03
The root mean square of the residuals (RMSR) is 0.04
The df corrected root mean square of the residuals is 0.05
Fit based upon off diagonal values = 0.99
print(fit$loadings, cutoff=0.3)
Loadings:
PA1 PA3 PA2 PA4
Q4_1 0.994
Q4_2 0.987
Q4_3 0.983
Q4_4 0.863
Q4_5 0.668
Q4_6 0.300
Q4_7 0.325
Q4_8 0.976
Q4_9 0.758
Q4_10 0.752
Q4_11 0.736
Q4_12 0.445 0.424
Q4_13 0.599 0.418
Q4_14 0.481
Q4_15 0.763
Q4_16 0.640
Q4_17 0.761
Q4_18 1.033
Q4_19 0.737
Q5_1 0.355 0.363
Q5_2 0.639
Q5_3 0.693
Q5_4 0.929
Q5_5 0.899
Q5_6 0.796
Q5_7 0.433 0.304
Q5_8 0.755
Q5_9 0.519
Q5_10 0.352
Q5_11
Q5_12 0.427
Q6_1 0.984
Q6_2 1.045
Q6_3 1.028
Q6_4 0.996
Q6_5 0.427
Q6_6 0.926
Q6_7 0.901
Q6_8 1.003
Q6_9 0.531
Q6_10 0.370
Q6_11 0.404 0.378
Q7_1 0.349
Q7_2 0.491
Q7_3 0.890
Q7_4 0.625
Q7_5 0.740
Q7_6 0.660
Q7_7 -0.333 0.957
Q7_8 0.703
Q7_9 0.301
Q7_10 0.390
Q7_11 0.571
Q7_12 0.791
Q7_13 0.817
Q7_14 0.832
Q7_15
PA1 PA3 PA2 PA4
SS loadings 11.819 9.051 7.625 5.243
Proportion Var 0.207 0.159 0.134 0.092
Cumulative Var 0.207 0.366 0.500 0.592
fit <- psych::fa(r = cov.dat, nfactors = 4, rotate = "Promax", fm = "pa", covar = T)
fit
Factor Analysis using method = pa
Call: psych::fa(r = cov.dat, nfactors = 4, rotate = "Promax", covar = T,
fm = "pa")
Unstandardized loadings (pattern matrix) based upon covariance matrix
PA1 PA3 PA2 PA4 h2 u2 H2 U2
Q4_1 0.81 -0.18 -0.09 0.03 0.43 0.32 0.57 0.43
Q4_2 0.79 -0.16 -0.07 0.01 0.43 0.25 0.63 0.37
Q4_3 0.77 -0.21 -0.02 0.02 0.40 0.30 0.57 0.43
Q4_4 0.64 -0.17 0.11 0.03 0.40 0.27 0.59 0.41
Q4_5 0.60 0.06 -0.09 0.08 0.41 0.37 0.52 0.48
Q4_6 0.27 0.08 0.13 0.26 0.41 0.55 0.43 0.57
Q4_7 0.06 -0.01 0.29 0.25 0.29 0.59 0.32 0.68
Q4_8 0.89 -0.03 -0.14 -0.09 0.52 0.34 0.61 0.39
Q4_9 0.78 -0.10 0.09 -0.14 0.48 0.53 0.48 0.52
Q4_10 0.56 -0.11 0.12 -0.01 0.32 0.31 0.51 0.49
Q4_11 0.73 -0.01 0.09 -0.07 0.55 0.36 0.60 0.40
Q4_12 0.52 0.37 0.01 -0.16 0.55 0.56 0.49 0.51
Q4_13 0.54 0.29 -0.17 -0.13 0.36 0.41 0.47 0.53
Q4_14 0.48 0.13 0.10 -0.02 0.40 0.40 0.50 0.50
Q4_15 0.73 0.03 -0.08 0.03 0.52 0.32 0.62 0.38
Q4_16 0.62 0.08 -0.21 0.19 0.46 0.42 0.52 0.48
Q4_17 0.74 0.05 -0.03 -0.14 0.46 0.47 0.50 0.50
Q4_18 0.84 -0.12 -0.10 0.02 0.50 0.18 0.73 0.27
Q4_19 0.76 -0.05 0.08 -0.04 0.58 0.36 0.62 0.38
Q5_1 0.35 -0.01 0.08 0.28 0.40 0.50 0.44 0.56
Q5_2 0.05 0.13 0.04 0.60 0.55 0.52 0.51 0.49
Q5_3 0.20 0.14 -0.14 0.61 0.58 0.51 0.53 0.47
Q5_4 -0.11 -0.16 0.09 0.97 0.78 0.45 0.64 0.36
Q5_5 -0.10 -0.23 0.08 0.91 0.63 0.44 0.59 0.41
Q5_6 0.08 0.01 0.01 0.66 0.54 0.28 0.65 0.35
Q5_7 -0.02 0.38 0.10 0.26 0.39 0.50 0.44 0.56
Q5_8 -0.05 0.13 0.08 0.71 0.67 0.45 0.60 0.40
Q5_9 0.20 0.29 -0.05 0.42 0.58 0.41 0.58 0.42
Q5_10 0.16 0.14 0.03 0.28 0.27 0.43 0.39 0.61
Q5_11 0.25 0.12 0.21 0.16 0.40 0.50 0.44 0.56
Q5_12 0.05 0.14 0.21 0.35 0.42 0.48 0.47 0.53
Q6_1 -0.05 0.76 -0.16 -0.04 0.39 0.32 0.55 0.45
Q6_2 -0.17 0.91 -0.13 0.03 0.55 0.28 0.66 0.34
Q6_3 -0.19 0.90 -0.14 0.05 0.53 0.33 0.62 0.38
Q6_4 -0.14 0.85 -0.17 0.02 0.46 0.40 0.54 0.46
Q6_5 0.07 0.38 0.19 -0.07 0.28 0.78 0.26 0.74
Q6_6 0.03 0.70 -0.03 -0.09 0.43 0.24 0.64 0.36
Q6_7 0.10 0.72 0.01 -0.15 0.52 0.24 0.68 0.32
Q6_8 0.00 0.84 0.01 -0.18 0.56 0.26 0.68 0.32
Q6_9 0.16 0.27 0.58 -0.31 0.52 0.97 0.35 0.65
Q6_10 0.07 0.24 0.32 -0.02 0.31 0.53 0.37 0.63
Q6_11 0.00 0.35 0.37 0.08 0.51 0.43 0.55 0.45
Q7_1 0.14 0.29 0.23 0.14 0.48 0.34 0.59 0.41
Q7_2 0.05 0.13 0.39 0.12 0.38 0.36 0.51 0.49
Q7_3 -0.20 -0.10 0.86 0.12 0.59 0.43 0.58 0.42
Q7_4 -0.02 0.13 0.56 0.04 0.44 0.52 0.46 0.54
Q7_5 0.15 0.04 0.66 -0.07 0.56 0.34 0.63 0.37
Q7_6 0.08 0.10 0.59 -0.05 0.46 0.38 0.55 0.45
Q7_7 -0.02 -0.28 0.90 0.11 0.65 0.38 0.63 0.37
Q7_8 0.13 -0.03 0.57 -0.04 0.39 0.38 0.50 0.50
Q7_9 0.32 0.18 0.23 0.06 0.49 0.50 0.50 0.50
Q7_10 0.38 0.27 0.11 0.00 0.47 0.42 0.52 0.48
Q7_11 0.22 -0.02 0.43 0.00 0.35 0.35 0.50 0.50
Q7_12 -0.01 -0.05 0.73 -0.03 0.46 0.59 0.44 0.56
Q7_13 -0.15 -0.12 0.73 -0.14 0.27 0.71 0.27 0.73
Q7_14 -0.19 -0.22 0.75 0.18 0.43 0.55 0.44 0.56
Q7_15 0.28 0.18 0.17 0.04 0.36 0.46 0.44 0.56
PA1 PA3 PA2 PA4
SS loadings 9.51 5.94 6.32 4.73
Proportion Var 0.19 0.12 0.12 0.09
Cumulative Var 0.19 0.30 0.43 0.52
Proportion Explained 0.36 0.22 0.24 0.18
Cumulative Proportion 0.36 0.58 0.82 1.00
Standardized loadings (pattern matrix)
item PA1 PA3 PA2 PA4 h2 u2
Q4_1 1 0.93 -0.21 -0.10 0.04 0.57 0.43
Q4_2 2 0.97 -0.19 -0.08 0.01 0.63 0.37
Q4_3 3 0.92 -0.25 -0.02 0.02 0.57 0.43
Q4_4 4 0.79 -0.21 0.13 0.04 0.59 0.41
Q4_5 5 0.68 0.06 -0.10 0.09 0.52 0.48
Q4_6 6 0.28 0.08 0.13 0.26 0.43 0.57
Q4_7 7 0.07 -0.01 0.31 0.26 0.32 0.68
Q4_8 8 0.95 -0.04 -0.15 -0.09 0.61 0.39
Q4_9 9 0.78 -0.10 0.09 -0.14 0.48 0.52
Q4_10 10 0.71 -0.14 0.15 -0.01 0.51 0.49
Q4_11 11 0.76 -0.01 0.10 -0.07 0.60 0.40
Q4_12 12 0.50 0.35 0.01 -0.15 0.49 0.51
Q4_13 13 0.62 0.33 -0.19 -0.14 0.47 0.53
Q4_14 14 0.53 0.14 0.11 -0.02 0.50 0.50
Q4_15 15 0.80 0.03 -0.09 0.03 0.62 0.38
Q4_16 16 0.66 0.09 -0.22 0.20 0.52 0.48
Q4_17 17 0.77 0.06 -0.03 -0.14 0.50 0.50
Q4_18 18 1.02 -0.14 -0.12 0.02 0.73 0.27
Q4_19 19 0.79 -0.05 0.09 -0.04 0.62 0.38
Q5_1 20 0.37 -0.01 0.08 0.30 0.44 0.56
Q5_2 21 0.05 0.12 0.04 0.58 0.51 0.49
Q5_3 22 0.19 0.14 -0.14 0.58 0.53 0.47
Q5_4 23 -0.10 -0.14 0.08 0.88 0.64 0.36
Q5_5 24 -0.10 -0.22 0.08 0.88 0.59 0.41
Q5_6 25 0.09 0.02 0.01 0.73 0.65 0.35
Q5_7 26 -0.02 0.40 0.10 0.27 0.44 0.56
Q5_8 27 -0.05 0.13 0.08 0.67 0.60 0.40
Q5_9 28 0.20 0.29 -0.05 0.42 0.58 0.42
Q5_10 29 0.19 0.16 0.03 0.33 0.39 0.61
Q5_11 30 0.26 0.12 0.22 0.16 0.44 0.56
Q5_12 31 0.05 0.15 0.22 0.37 0.47 0.53
Q6_1 32 -0.05 0.90 -0.19 -0.04 0.55 0.45
Q6_2 33 -0.18 1.00 -0.15 0.03 0.66 0.34
Q6_3 34 -0.20 0.97 -0.15 0.05 0.62 0.38
Q6_4 35 -0.15 0.92 -0.18 0.02 0.54 0.46
Q6_5 36 0.07 0.37 0.18 -0.07 0.26 0.74
Q6_6 37 0.04 0.85 -0.04 -0.11 0.64 0.36
Q6_7 38 0.11 0.83 0.01 -0.17 0.68 0.32
Q6_8 39 -0.01 0.92 0.01 -0.20 0.68 0.32
Q6_9 40 0.13 0.22 0.47 -0.26 0.35 0.65
Q6_10 41 0.08 0.27 0.35 -0.02 0.37 0.63
Q6_11 42 0.01 0.36 0.38 0.09 0.55 0.45
Q7_1 43 0.15 0.32 0.25 0.16 0.59 0.41
Q7_2 44 0.06 0.15 0.46 0.14 0.51 0.49
Q7_3 45 -0.19 -0.10 0.85 0.12 0.58 0.42
Q7_4 46 -0.02 0.14 0.57 0.05 0.46 0.54
Q7_5 47 0.16 0.04 0.70 -0.08 0.63 0.37
Q7_6 48 0.08 0.11 0.64 -0.05 0.55 0.45
Q7_7 49 -0.02 -0.28 0.88 0.11 0.63 0.37
Q7_8 50 0.15 -0.04 0.65 -0.05 0.50 0.50
Q7_9 51 0.33 0.18 0.23 0.06 0.50 0.50
Q7_10 52 0.40 0.28 0.11 0.00 0.52 0.48
Q7_11 53 0.26 -0.02 0.52 0.00 0.50 0.50
Q7_12 54 -0.01 -0.05 0.72 -0.03 0.44 0.56
Q7_13 55 -0.15 -0.12 0.74 -0.14 0.27 0.73
Q7_14 56 -0.19 -0.22 0.76 0.18 0.44 0.56
Q7_15 57 0.31 0.20 0.19 0.04 0.44 0.56
PA1 PA3 PA2 PA4
SS loadings 10.68 6.66 7.10 5.32
Proportion Var 0.19 0.12 0.12 0.09
Cumulative Var 0.19 0.30 0.43 0.52
Cum. factor Var 0.36 0.58 0.82 1.00
With factor correlations of
PA1 PA3 PA2 PA4
PA1 1.00 0.73 0.70 0.65
PA3 0.73 1.00 0.63 0.58
PA2 0.70 0.63 1.00 0.65
PA4 0.65 0.58 0.65 1.00
Mean item complexity = 1.5
Test of the hypothesis that 4 factors are sufficient.
The degrees of freedom for the null model are 1596 and the objective function was 46.33
The degrees of freedom for the model are 1374 and the objective function was 10.73
The root mean square of the residuals (RMSR) is 0.04
The df corrected root mean square of the residuals is 0.04
Fit based upon off diagonal values = 0.99
Measures of factor score adequacy
PA1 PA3 PA2 PA4
Correlation of (regression) scores with factors 0.98 0.98 0.97 0.96
Multiple R square of scores with factors 0.97 0.95 0.94 0.92
Minimum correlation of possible factor scores 0.94 0.91 0.87 0.84
print(fit$loadings, cutoff=0.3)
Loadings:
PA1 PA3 PA2 PA4
Q4_1 0.806
Q4_2 0.794
Q4_3 0.769
Q4_4 0.645
Q4_5 0.602
Q4_6
Q4_7
Q4_8 0.885
Q4_9 0.783
Q4_10 0.560
Q4_11 0.727
Q4_12 0.522 0.371
Q4_13 0.543
Q4_14 0.478
Q4_15 0.732
Q4_16 0.621
Q4_17 0.741
Q4_18 0.838
Q4_19 0.762
Q5_1 0.355
Q5_2 0.597
Q5_3 0.610
Q5_4 0.970
Q5_5 0.912
Q5_6 0.664
Q5_7 0.376
Q5_8 0.710
Q5_9 0.423
Q5_10
Q5_11
Q5_12 0.351
Q6_1 0.763
Q6_2 0.908
Q6_3 0.897
Q6_4 0.851
Q6_5 0.382
Q6_6 0.700
Q6_7 0.725
Q6_8 0.835
Q6_9 0.578 -0.312
Q6_10 0.317
Q6_11 0.353 0.369
Q7_1
Q7_2 0.394
Q7_3 0.865
Q7_4 0.558
Q7_5 0.660
Q7_6 0.591
Q7_7 0.896
Q7_8 0.571
Q7_9 0.323
Q7_10 0.383
Q7_11 0.434
Q7_12 0.734
Q7_13 0.732
Q7_14 0.751
Q7_15
PA1 PA3 PA2 PA4
SS loadings 9.520 6.311 6.238 4.572
Proportion Var 0.167 0.111 0.109 0.080
Cumulative Var 0.167 0.278 0.387 0.467
fit <- psych::fa(r = corr.pc$rho, nfactors = 5, rotate = "Promax", fm = "pa")
fit
Factor Analysis using method = pa
Call: psych::fa(r = corr.pc$rho, nfactors = 5, rotate = "Promax", fm = "pa")
Standardized loadings (pattern matrix) based upon correlation matrix
PA1 PA3 PA2 PA4 PA5 h2 u2 com
Q4_1 1.02 -0.17 -0.13 0.01 -0.07 0.67 0.33 1.1
Q4_2 0.99 -0.16 -0.08 0.04 -0.01 0.72 0.28 1.1
Q4_3 1.01 -0.21 -0.05 -0.01 -0.08 0.67 0.33 1.1
Q4_4 0.94 -0.10 0.05 -0.03 -0.25 0.77 0.23 1.2
Q4_5 0.67 0.09 -0.10 0.14 0.02 0.59 0.41 1.2
Q4_6 0.30 0.10 0.11 0.29 -0.12 0.49 0.51 2.8
Q4_7 0.06 0.06 0.29 0.27 -0.16 0.36 0.64 2.7
Q4_8 0.97 -0.02 -0.13 -0.09 0.07 0.68 0.32 1.1
Q4_9 0.74 -0.09 0.14 -0.12 0.10 0.53 0.47 1.2
Q4_10 0.79 -0.04 0.11 -0.05 -0.13 0.63 0.37 1.1
Q4_11 0.72 -0.01 0.15 -0.04 0.10 0.67 0.33 1.1
Q4_12 0.39 0.34 0.09 -0.09 0.28 0.63 0.37 3.1
Q4_13 0.53 0.31 -0.10 -0.07 0.38 0.70 0.30 2.6
Q4_14 0.42 0.12 0.17 0.05 0.28 0.63 0.37 2.3
Q4_15 0.73 0.00 -0.03 0.10 0.18 0.69 0.31 1.2
Q4_16 0.63 0.11 -0.22 0.25 0.08 0.59 0.41 1.7
Q4_17 0.75 0.08 -0.01 -0.11 0.06 0.56 0.44 1.1
Q4_18 1.02 -0.13 -0.11 0.07 0.05 0.83 0.17 1.1
Q4_19 0.71 -0.03 0.15 0.00 0.13 0.68 0.32 1.2
Q5_1 0.32 -0.07 0.12 0.39 0.14 0.52 0.48 2.5
Q5_2 -0.01 0.09 0.02 0.66 0.09 0.56 0.44 1.1
Q5_3 0.09 0.05 -0.11 0.74 0.21 0.66 0.34 1.2
Q5_4 -0.08 -0.21 0.08 0.93 -0.08 0.67 0.33 1.2
Q5_5 -0.05 -0.27 0.06 0.89 -0.13 0.60 0.40 1.2
Q5_6 0.09 -0.04 0.00 0.80 -0.01 0.70 0.30 1.0
Q5_7 -0.09 0.40 0.13 0.32 0.07 0.50 0.50 2.3
Q5_8 -0.09 0.07 0.08 0.76 0.00 0.65 0.35 1.1
Q5_9 0.15 0.26 -0.05 0.53 0.05 0.66 0.34 1.7
Q5_10 0.18 0.18 0.03 0.36 0.01 0.45 0.55 2.1
Q5_11 0.20 0.08 0.27 0.25 0.05 0.51 0.49 3.1
Q5_12 0.01 0.16 0.20 0.43 -0.04 0.51 0.49 1.8
Q6_1 -0.09 0.95 -0.18 -0.01 0.14 0.67 0.33 1.1
Q6_2 -0.21 1.07 -0.18 0.06 -0.02 0.73 0.27 1.1
Q6_3 -0.18 1.05 -0.18 0.06 -0.03 0.72 0.28 1.1
Q6_4 -0.16 1.03 -0.23 0.01 -0.06 0.63 0.37 1.2
Q6_5 0.02 0.40 0.20 -0.03 0.08 0.33 0.67 1.6
Q6_6 0.04 0.96 -0.05 -0.12 -0.07 0.77 0.23 1.1
Q6_7 0.09 0.90 0.01 -0.17 0.03 0.78 0.22 1.1
Q6_8 -0.06 1.01 0.01 -0.19 -0.01 0.77 0.23 1.1
Q6_9 -0.02 0.16 0.64 -0.21 0.30 0.53 0.47 1.8
Q6_10 0.02 0.24 0.40 0.03 0.08 0.41 0.59 1.8
Q6_11 -0.04 0.38 0.39 0.12 0.03 0.59 0.41 2.2
Q7_1 0.13 0.38 0.25 0.17 -0.10 0.67 0.33 2.7
Q7_2 0.08 0.23 0.46 0.10 -0.14 0.58 0.42 1.9
Q7_3 -0.20 -0.08 0.88 0.11 -0.13 0.60 0.40 1.2
Q7_4 0.02 0.28 0.55 -0.03 -0.38 0.63 0.37 2.4
Q7_5 0.17 0.10 0.71 -0.11 -0.15 0.69 0.31 1.3
Q7_6 0.06 0.11 0.67 -0.04 0.00 0.59 0.41 1.1
Q7_7 -0.03 -0.36 0.98 0.14 -0.01 0.72 0.28 1.3
Q7_8 0.15 -0.01 0.68 -0.06 -0.12 0.55 0.45 1.2
Q7_9 0.34 0.26 0.22 0.06 -0.16 0.58 0.42 3.3
Q7_10 0.45 0.37 0.10 -0.01 -0.23 0.66 0.34 2.6
Q7_11 0.33 0.07 0.52 -0.08 -0.23 0.62 0.38 2.3
Q7_12 -0.07 -0.14 0.85 -0.02 0.11 0.53 0.47 1.1
Q7_13 -0.24 -0.26 0.90 -0.10 0.13 0.38 0.62 1.4
Q7_14 -0.18 -0.31 0.84 0.18 -0.07 0.48 0.52 1.5
Q7_15 0.33 0.29 0.17 0.03 -0.20 0.54 0.46 3.2
PA1 PA3 PA2 PA4 PA5
SS loadings 11.88 8.37 7.60 5.75 1.18
Proportion Var 0.21 0.15 0.13 0.10 0.02
Cumulative Var 0.21 0.36 0.49 0.59 0.61
Proportion Explained 0.34 0.24 0.22 0.17 0.03
Cumulative Proportion 0.34 0.58 0.80 0.97 1.00
With factor correlations of
PA1 PA3 PA2 PA4 PA5
PA1 1.00 0.74 0.71 0.68 0.17
PA3 0.74 1.00 0.66 0.64 0.22
PA2 0.71 0.66 1.00 0.69 0.12
PA4 0.68 0.64 0.69 1.00 0.09
PA5 0.17 0.22 0.12 0.09 1.00
Mean item complexity = 1.6
Test of the hypothesis that 5 factors are sufficient.
The degrees of freedom for the null model are 1596 and the objective function was 84.54
The degrees of freedom for the model are 1321 and the objective function was 40.74
The root mean square of the residuals (RMSR) is 0.04
The df corrected root mean square of the residuals is 0.04
Fit based upon off diagonal values = 0.99
print(fit$loadings, cutoff=0.3)
Loadings:
PA1 PA3 PA2 PA4 PA5
Q4_1 1.017
Q4_2 0.991
Q4_3 1.007
Q4_4 0.936
Q4_5 0.666
Q4_6
Q4_7
Q4_8 0.965
Q4_9 0.739
Q4_10 0.787
Q4_11 0.716
Q4_12 0.390 0.338
Q4_13 0.533 0.308 0.382
Q4_14 0.424
Q4_15 0.729
Q4_16 0.625
Q4_17 0.751
Q4_18 1.024
Q4_19 0.710
Q5_1 0.321 0.388
Q5_2 0.662
Q5_3 0.740
Q5_4 0.930
Q5_5 0.895
Q5_6 0.803
Q5_7 0.404 0.317
Q5_8 0.764
Q5_9 0.528
Q5_10 0.358
Q5_11
Q5_12 0.430
Q6_1 0.950
Q6_2 1.066
Q6_3 1.049
Q6_4 1.033
Q6_5 0.396
Q6_6 0.964
Q6_7 0.898
Q6_8 1.015
Q6_9 0.643
Q6_10 0.396
Q6_11 0.384 0.387
Q7_1 0.382
Q7_2 0.457
Q7_3 0.876
Q7_4 0.550 -0.384
Q7_5 0.710
Q7_6 0.669
Q7_7 -0.363 0.977
Q7_8 0.682
Q7_9 0.335
Q7_10 0.445 0.374
Q7_11 0.332 0.519
Q7_12 0.851
Q7_13 0.897
Q7_14 -0.306 0.836
Q7_15 0.334
PA1 PA3 PA2 PA4 PA5
SS loadings 11.823 9.105 7.726 5.384 1.195
Proportion Var 0.207 0.160 0.136 0.094 0.021
Cumulative Var 0.207 0.367 0.503 0.597 0.618
fit <- psych::fa(r = cov.dat, nfactors = 5, rotate = "Promax", fm = "pa", covar = T)
fit
Factor Analysis using method = pa
Call: psych::fa(r = cov.dat, nfactors = 5, rotate = "Promax", covar = T,
fm = "pa")
Unstandardized loadings (pattern matrix) based upon covariance matrix
PA1 PA3 PA4 PA2 PA5 h2 u2 H2 U2
Q4_1 0.82 -0.09 0.01 -0.04 -0.16 0.44 0.31 0.59 0.41
Q4_2 0.79 -0.11 0.01 -0.04 -0.07 0.43 0.24 0.64 0.36
Q4_3 0.79 -0.12 -0.01 0.02 -0.14 0.42 0.28 0.60 0.40
Q4_4 0.70 -0.02 -0.02 0.17 -0.24 0.45 0.22 0.67 0.33
Q4_5 0.58 0.05 0.09 -0.07 -0.01 0.41 0.37 0.52 0.48
Q4_6 0.29 0.14 0.25 0.15 -0.12 0.42 0.54 0.44 0.56
Q4_7 0.10 0.08 0.23 0.31 -0.13 0.30 0.58 0.35 0.65
Q4_8 0.86 -0.01 -0.09 -0.11 -0.02 0.52 0.34 0.61 0.39
Q4_9 0.75 -0.10 -0.14 0.07 0.09 0.48 0.53 0.47 0.53
Q4_10 0.60 0.00 -0.05 0.15 -0.15 0.34 0.28 0.55 0.45
Q4_11 0.69 -0.04 -0.06 0.07 0.12 0.55 0.36 0.60 0.40
Q4_12 0.46 0.23 -0.12 -0.05 0.30 0.57 0.54 0.51 0.49
Q4_13 0.47 0.14 -0.08 -0.22 0.27 0.39 0.38 0.51 0.49
Q4_14 0.41 -0.01 0.03 0.02 0.30 0.43 0.37 0.54 0.46
Q4_15 0.68 -0.05 0.06 -0.10 0.15 0.53 0.31 0.63 0.37
Q4_16 0.60 0.07 0.21 -0.18 -0.04 0.46 0.42 0.52 0.48
Q4_17 0.72 0.06 -0.14 -0.02 0.03 0.46 0.47 0.50 0.50
Q4_18 0.82 -0.10 0.02 -0.08 -0.02 0.50 0.18 0.73 0.27
Q4_19 0.72 -0.08 -0.02 0.05 0.12 0.58 0.36 0.62 0.38
Q5_1 0.28 -0.15 0.36 0.00 0.24 0.44 0.46 0.49 0.51
Q5_2 0.01 0.05 0.67 0.01 0.05 0.56 0.51 0.52 0.48
Q5_3 0.10 -0.07 0.76 -0.22 0.24 0.68 0.41 0.62 0.38
Q5_4 -0.08 -0.09 1.01 0.14 -0.27 0.78 0.45 0.63 0.37
Q5_5 -0.07 -0.13 0.94 0.14 -0.31 0.63 0.44 0.59 0.41
Q5_6 0.06 -0.02 0.72 0.01 -0.05 0.54 0.28 0.66 0.34
Q5_7 -0.05 0.27 0.30 0.06 0.15 0.40 0.49 0.45 0.55
Q5_8 -0.08 0.07 0.78 0.07 0.01 0.67 0.44 0.60 0.40
Q5_9 0.14 0.17 0.50 -0.07 0.13 0.60 0.39 0.60 0.40
Q5_10 0.14 0.10 0.31 0.02 0.03 0.28 0.43 0.39 0.61
Q5_11 0.21 0.03 0.20 0.15 0.18 0.41 0.50 0.45 0.55
Q5_12 0.04 0.12 0.38 0.19 0.02 0.42 0.48 0.47 0.53
Q6_1 -0.06 0.68 -0.02 -0.15 0.08 0.39 0.32 0.55 0.45
Q6_2 -0.13 0.93 0.02 -0.07 -0.12 0.58 0.25 0.69 0.31
Q6_3 -0.15 0.92 0.04 -0.08 -0.12 0.56 0.30 0.65 0.35
Q6_4 -0.10 0.92 0.00 -0.09 -0.18 0.51 0.35 0.59 0.41
Q6_5 0.02 0.25 -0.04 0.12 0.28 0.30 0.77 0.28 0.72
Q6_6 0.04 0.68 -0.09 -0.01 0.02 0.43 0.24 0.64 0.36
Q6_7 0.10 0.67 -0.15 0.01 0.10 0.52 0.24 0.68 0.32
Q6_8 0.00 0.78 -0.18 0.01 0.10 0.56 0.26 0.68 0.32
Q6_9 0.01 -0.05 -0.28 0.38 0.84 0.74 0.75 0.50 0.50
Q6_10 0.02 0.11 0.02 0.22 0.33 0.33 0.50 0.40 0.60
Q6_11 -0.02 0.26 0.11 0.29 0.23 0.52 0.42 0.55 0.45
Q7_1 0.13 0.26 0.16 0.20 0.08 0.48 0.34 0.59 0.41
Q7_2 0.07 0.16 0.11 0.37 0.01 0.38 0.35 0.52 0.48
Q7_3 -0.15 -0.01 0.09 0.80 0.02 0.61 0.42 0.59 0.41
Q7_4 0.06 0.30 -0.02 0.58 -0.18 0.52 0.44 0.54 0.46
Q7_5 0.18 0.08 -0.10 0.59 0.10 0.57 0.33 0.63 0.37
Q7_6 0.08 0.09 -0.05 0.51 0.17 0.46 0.38 0.55 0.45
Q7_7 0.00 -0.23 0.10 0.80 0.11 0.65 0.38 0.63 0.37
Q7_8 0.14 -0.01 -0.05 0.50 0.11 0.39 0.38 0.50 0.50
Q7_9 0.33 0.19 0.06 0.21 0.03 0.49 0.49 0.50 0.50
Q7_10 0.40 0.31 -0.02 0.12 -0.05 0.48 0.41 0.54 0.46
Q7_11 0.25 0.06 -0.03 0.42 -0.04 0.37 0.34 0.52 0.48
Q7_12 -0.04 -0.13 -0.01 0.60 0.33 0.47 0.58 0.45 0.55
Q7_13 -0.20 -0.24 -0.12 0.58 0.42 0.30 0.68 0.31 0.69
Q7_14 -0.16 -0.17 0.18 0.67 0.07 0.43 0.55 0.44 0.56
Q7_15 0.29 0.20 0.04 0.16 0.01 0.36 0.46 0.44 0.56
PA1 PA3 PA4 PA2 PA5
SS loadings 9.10 5.24 5.22 5.46 2.46
Proportion Var 0.18 0.10 0.10 0.11 0.05
Cumulative Var 0.18 0.28 0.39 0.49 0.54
Proportion Explained 0.33 0.19 0.19 0.20 0.09
Cumulative Proportion 0.33 0.52 0.71 0.91 1.00
Standardized loadings (pattern matrix)
item PA1 PA3 PA4 PA2 PA5 h2 u2
Q4_1 1 0.95 -0.11 0.01 -0.04 -0.18 0.59 0.41
Q4_2 2 0.96 -0.13 0.01 -0.05 -0.08 0.64 0.36
Q4_3 3 0.94 -0.14 -0.01 0.03 -0.17 0.60 0.40
Q4_4 4 0.86 -0.02 -0.02 0.20 -0.29 0.67 0.33
Q4_5 5 0.66 0.06 0.10 -0.08 -0.01 0.52 0.48
Q4_6 6 0.30 0.14 0.26 0.16 -0.12 0.44 0.56
Q4_7 7 0.11 0.09 0.25 0.33 -0.14 0.35 0.65
Q4_8 8 0.93 -0.01 -0.10 -0.12 -0.02 0.61 0.39
Q4_9 9 0.75 -0.10 -0.14 0.07 0.09 0.47 0.53
Q4_10 10 0.75 0.00 -0.06 0.19 -0.19 0.55 0.45
Q4_11 11 0.73 -0.04 -0.06 0.07 0.12 0.60 0.40
Q4_12 12 0.43 0.22 -0.12 -0.05 0.28 0.51 0.49
Q4_13 13 0.54 0.15 -0.09 -0.25 0.31 0.51 0.49
Q4_14 14 0.46 -0.02 0.03 0.02 0.33 0.54 0.46
Q4_15 15 0.74 -0.06 0.07 -0.11 0.16 0.63 0.37
Q4_16 16 0.63 0.08 0.22 -0.19 -0.05 0.52 0.48
Q4_17 17 0.75 0.06 -0.15 -0.02 0.03 0.50 0.50
Q4_18 18 0.99 -0.12 0.03 -0.10 -0.03 0.73 0.27
Q4_19 19 0.74 -0.09 -0.02 0.05 0.13 0.62 0.38
Q5_1 20 0.30 -0.16 0.38 0.00 0.26 0.49 0.51
Q5_2 21 0.01 0.05 0.65 0.01 0.04 0.52 0.48
Q5_3 22 0.10 -0.06 0.72 -0.21 0.23 0.62 0.38
Q5_4 23 -0.07 -0.08 0.91 0.13 -0.24 0.63 0.37
Q5_5 24 -0.07 -0.13 0.91 0.13 -0.30 0.59 0.41
Q5_6 25 0.07 -0.02 0.80 0.02 -0.06 0.66 0.34
Q5_7 26 -0.05 0.29 0.32 0.06 0.16 0.45 0.55
Q5_8 27 -0.07 0.06 0.74 0.06 0.01 0.60 0.40
Q5_9 28 0.14 0.17 0.50 -0.07 0.13 0.60 0.40
Q5_10 29 0.16 0.11 0.37 0.02 0.04 0.39 0.61
Q5_11 30 0.22 0.03 0.21 0.16 0.19 0.45 0.55
Q5_12 31 0.04 0.12 0.40 0.20 0.03 0.47 0.53
Q6_1 32 -0.07 0.81 -0.02 -0.18 0.09 0.55 0.45
Q6_2 33 -0.15 1.03 0.02 -0.08 -0.13 0.69 0.31
Q6_3 34 -0.16 1.00 0.04 -0.08 -0.13 0.65 0.35
Q6_4 35 -0.11 0.99 0.00 -0.10 -0.20 0.59 0.41
Q6_5 36 0.02 0.25 -0.04 0.11 0.27 0.28 0.72
Q6_6 37 0.05 0.83 -0.11 -0.02 0.02 0.64 0.36
Q6_7 38 0.11 0.77 -0.17 0.01 0.11 0.68 0.32
Q6_8 39 0.00 0.86 -0.20 0.01 0.11 0.68 0.32
Q6_9 40 0.01 -0.04 -0.23 0.31 0.68 0.50 0.50
Q6_10 41 0.02 0.12 0.02 0.24 0.36 0.40 0.60
Q6_11 42 -0.02 0.27 0.12 0.30 0.24 0.55 0.45
Q7_1 43 0.14 0.29 0.18 0.22 0.09 0.59 0.41
Q7_2 44 0.09 0.19 0.13 0.43 0.01 0.52 0.48
Q7_3 45 -0.15 -0.01 0.09 0.79 0.02 0.59 0.41
Q7_4 46 0.06 0.31 -0.02 0.60 -0.18 0.54 0.46
Q7_5 47 0.18 0.08 -0.10 0.63 0.10 0.63 0.37
Q7_6 48 0.08 0.09 -0.06 0.55 0.18 0.55 0.45
Q7_7 49 0.00 -0.22 0.10 0.78 0.11 0.63 0.37
Q7_8 50 0.16 -0.01 -0.06 0.57 0.13 0.50 0.50
Q7_9 51 0.33 0.19 0.06 0.22 0.03 0.50 0.50
Q7_10 52 0.42 0.33 -0.02 0.13 -0.05 0.54 0.46
Q7_11 53 0.30 0.07 -0.03 0.50 -0.04 0.52 0.48
Q7_12 54 -0.04 -0.13 -0.01 0.58 0.33 0.45 0.55
Q7_13 55 -0.20 -0.24 -0.12 0.58 0.43 0.31 0.69
Q7_14 56 -0.16 -0.18 0.18 0.68 0.07 0.44 0.56
Q7_15 57 0.32 0.22 0.04 0.18 0.01 0.44 0.56
PA1 PA3 PA4 PA2 PA5
SS loadings 10.22 5.88 5.86 6.14 2.76
Proportion Var 0.18 0.10 0.10 0.11 0.05
Cumulative Var 0.18 0.28 0.39 0.49 0.54
Cum. factor Var 0.33 0.52 0.71 0.91 1.00
With factor correlations of
PA1 PA3 PA4 PA2 PA5
PA1 1.00 0.70 0.69 0.61 0.62
PA3 0.70 1.00 0.62 0.51 0.65
PA4 0.69 0.62 1.00 0.63 0.58
PA2 0.61 0.51 0.63 1.00 0.42
PA5 0.62 0.65 0.58 0.42 1.00
Mean item complexity = 1.7
Test of the hypothesis that 5 factors are sufficient.
The degrees of freedom for the null model are 1596 and the objective function was 46.33
The degrees of freedom for the model are 1321 and the objective function was 9.85
The root mean square of the residuals (RMSR) is 0.03
The df corrected root mean square of the residuals is 0.04
Fit based upon off diagonal values = 0.99
Measures of factor score adequacy
PA1 PA3 PA4 PA2 PA5
Correlation of (regression) scores with factors 0.98 0.98 0.97 0.96 0.92
Multiple R square of scores with factors 0.97 0.95 0.93 0.92 0.84
Minimum correlation of possible factor scores 0.94 0.90 0.87 0.84 0.68
print(fit$loadings, cutoff=0.3)
Loadings:
PA1 PA3 PA4 PA2 PA5
Q4_1 0.820
Q4_2 0.785
Q4_3 0.785
Q4_4 0.701
Q4_5 0.583
Q4_6
Q4_7 0.311
Q4_8 0.865
Q4_9 0.754
Q4_10 0.595
Q4_11 0.692
Q4_12 0.456
Q4_13 0.470
Q4_14 0.409
Q4_15 0.676
Q4_16 0.597
Q4_17 0.723
Q4_18 0.815
Q4_19 0.721
Q5_1 0.360
Q5_2 0.672
Q5_3 0.757
Q5_4 1.009
Q5_5 0.941 -0.310
Q5_6 0.722
Q5_7 0.302
Q5_8 0.783
Q5_9 0.496
Q5_10 0.312
Q5_11
Q5_12 0.383
Q6_1 0.682
Q6_2 0.935
Q6_3 0.924
Q6_4 0.917
Q6_5
Q6_6 0.679
Q6_7 0.671
Q6_8 0.777
Q6_9 0.383 0.836
Q6_10 0.328
Q6_11
Q7_1
Q7_2 0.368
Q7_3 0.802
Q7_4 0.584
Q7_5 0.595
Q7_6 0.509
Q7_7 0.796
Q7_8 0.504
Q7_9 0.326
Q7_10 0.401 0.310
Q7_11 0.418
Q7_12 0.596 0.333
Q7_13 0.578 0.422
Q7_14 0.670
Q7_15
PA1 PA3 PA4 PA2 PA5
SS loadings 8.951 5.582 5.349 4.857 2.260
Proportion Var 0.157 0.098 0.094 0.085 0.040
Cumulative Var 0.157 0.255 0.349 0.434 0.474
fit <- psych::fa(r = corr.pc$rho, nfactors = 6,
rotate = "Promax", fm = "pa")
fit
Factor Analysis using method = pa
Call: psych::fa(r = corr.pc$rho, nfactors = 6, rotate = "Promax", fm = "pa")
Standardized loadings (pattern matrix) based upon correlation matrix
PA1 PA6 PA2 PA4 PA5 PA3 h2 u2 com
Q4_1 0.85 -0.12 -0.10 0.01 0.18 -0.07 0.67 0.33 1.2
Q4_2 0.82 -0.14 -0.08 0.03 0.15 0.05 0.72 0.28 1.2
Q4_3 0.86 -0.13 -0.02 0.00 0.14 -0.08 0.68 0.32 1.1
Q4_4 0.83 0.00 0.11 -0.02 0.21 -0.30 0.78 0.22 1.4
Q4_5 0.52 0.03 -0.12 0.13 0.18 0.10 0.59 0.41 1.6
Q4_6 0.30 0.15 0.16 0.29 0.06 -0.15 0.50 0.50 3.7
Q4_7 0.15 0.20 0.38 0.28 -0.09 -0.23 0.42 0.58 3.8
Q4_8 0.86 0.04 -0.05 -0.08 -0.06 0.11 0.69 0.31 1.1
Q4_9 0.65 -0.04 0.14 -0.11 -0.06 0.18 0.53 0.47 1.4
Q4_10 0.77 0.11 0.21 -0.04 -0.03 -0.18 0.68 0.32 1.3
Q4_11 0.63 0.02 0.14 -0.03 -0.02 0.20 0.67 0.33 1.3
Q4_12 0.39 0.33 0.13 -0.08 -0.28 0.43 0.65 0.35 4.0
Q4_13 0.42 0.18 -0.14 -0.07 -0.13 0.60 0.71 0.29 2.3
Q4_14 0.37 0.09 0.13 0.05 -0.16 0.45 0.62 0.38 2.5
Q4_15 0.62 0.00 -0.02 0.10 -0.06 0.29 0.69 0.31 1.5
Q4_16 0.57 0.15 -0.13 0.25 -0.09 0.09 0.60 0.40 1.8
Q4_17 0.67 0.10 0.03 -0.10 -0.02 0.12 0.56 0.44 1.2
Q4_18 0.87 -0.09 -0.08 0.07 0.04 0.11 0.83 0.17 1.1
Q4_19 0.63 0.01 0.15 0.00 -0.08 0.24 0.69 0.31 1.4
Q5_1 0.16 -0.21 -0.04 0.37 0.22 0.33 0.57 0.43 3.8
Q5_2 -0.01 0.07 0.03 0.64 -0.05 0.15 0.56 0.44 1.2
Q5_3 -0.02 -0.08 -0.19 0.72 0.05 0.36 0.69 0.31 1.7
Q5_4 -0.01 -0.07 0.18 0.91 -0.13 -0.16 0.69 0.31 1.2
Q5_5 0.01 -0.12 0.15 0.87 -0.08 -0.22 0.61 0.39 1.3
Q5_6 0.07 -0.02 0.02 0.77 0.02 0.01 0.70 0.30 1.0
Q5_7 -0.04 0.36 0.14 0.31 -0.07 0.16 0.50 0.50 2.9
Q5_8 -0.09 0.04 0.07 0.73 0.06 0.05 0.65 0.35 1.1
Q5_9 0.05 0.11 -0.13 0.50 0.23 0.17 0.68 0.32 1.9
Q5_10 0.12 0.11 -0.01 0.34 0.13 0.10 0.45 0.55 2.0
Q5_11 0.08 -0.05 0.10 0.24 0.28 0.22 0.53 0.47 3.5
Q5_12 -0.03 0.08 0.12 0.41 0.20 0.04 0.51 0.49 1.8
Q6_1 -0.08 0.74 -0.17 -0.01 0.05 0.24 0.67 0.33 1.4
Q6_2 -0.10 0.96 -0.06 0.07 -0.03 -0.04 0.76 0.24 1.0
Q6_3 -0.04 1.00 -0.02 0.08 -0.13 -0.07 0.79 0.21 1.1
Q6_4 -0.04 0.97 -0.07 0.02 -0.08 -0.11 0.68 0.32 1.1
Q6_5 -0.06 0.20 0.05 -0.04 0.26 0.26 0.35 0.65 3.1
Q6_6 0.02 0.73 -0.08 -0.11 0.29 0.04 0.76 0.24 1.4
Q6_7 0.11 0.75 0.03 -0.16 0.06 0.13 0.78 0.22 1.2
Q6_8 -0.04 0.80 -0.01 -0.18 0.18 0.11 0.76 0.24 1.2
Q6_9 -0.05 0.04 0.43 -0.20 -0.02 0.58 0.53 0.47 2.2
Q6_10 -0.06 0.09 0.22 0.02 0.23 0.27 0.42 0.58 3.2
Q6_11 -0.02 0.30 0.31 0.12 0.08 0.16 0.59 0.41 3.0
Q7_1 -0.04 0.12 0.01 0.15 0.63 0.08 0.73 0.27 1.2
Q7_2 0.04 0.15 0.33 0.09 0.31 -0.04 0.57 0.43 2.6
Q7_3 -0.05 0.11 0.89 0.12 -0.18 -0.12 0.68 0.32 1.2
Q7_4 -0.02 0.19 0.40 -0.03 0.54 -0.33 0.62 0.38 2.9
Q7_5 0.10 0.02 0.51 -0.11 0.38 0.01 0.69 0.31 2.1
Q7_6 0.09 0.13 0.57 -0.03 0.01 0.13 0.60 0.40 1.3
Q7_7 0.08 -0.16 0.93 0.14 -0.21 0.06 0.78 0.22 1.2
Q7_8 0.08 -0.08 0.48 -0.06 0.33 0.04 0.55 0.45 1.9
Q7_9 0.09 -0.04 -0.07 0.02 0.82 0.02 0.70 0.30 1.0
Q7_10 0.19 0.08 -0.16 -0.04 0.88 -0.10 0.77 0.23 1.2
Q7_11 0.18 -0.06 0.29 -0.09 0.59 -0.10 0.64 0.36 1.9
Q7_12 -0.10 -0.18 0.61 -0.02 0.11 0.32 0.53 0.47 1.9
Q7_13 -0.19 -0.21 0.71 -0.10 -0.09 0.29 0.37 0.63 1.8
Q7_14 -0.08 -0.14 0.78 0.18 -0.12 -0.05 0.50 0.50 1.3
Q7_15 0.10 0.01 -0.09 0.00 0.82 -0.06 0.64 0.36 1.1
PA1 PA6 PA2 PA4 PA5 PA3
SS loadings 9.63 6.37 5.74 5.54 5.12 3.52
Proportion Var 0.17 0.11 0.10 0.10 0.09 0.06
Cumulative Var 0.17 0.28 0.38 0.48 0.57 0.63
Proportion Explained 0.27 0.18 0.16 0.15 0.14 0.10
Cumulative Proportion 0.27 0.45 0.61 0.76 0.90 1.00
With factor correlations of
PA1 PA6 PA2 PA4 PA5 PA3
PA1 1.00 0.60 0.56 0.63 0.69 0.59
PA6 0.60 1.00 0.46 0.55 0.66 0.61
PA2 0.56 0.46 1.00 0.60 0.68 0.46
PA4 0.63 0.55 0.60 1.00 0.66 0.52
PA5 0.69 0.66 0.68 0.66 1.00 0.66
PA3 0.59 0.61 0.46 0.52 0.66 1.00
Mean item complexity = 1.8
Test of the hypothesis that 6 factors are sufficient.
The degrees of freedom for the null model are 1596 and the objective function was 84.54
The degrees of freedom for the model are 1269 and the objective function was 39.16
The root mean square of the residuals (RMSR) is 0.04
The df corrected root mean square of the residuals is 0.04
Fit based upon off diagonal values = 0.99
print(fit$loadings, cutoff=0.3)
Loadings:
PA1 PA6 PA2 PA4 PA5 PA3
Q4_1 0.849
Q4_2 0.815
Q4_3 0.859
Q4_4 0.835
Q4_5 0.523
Q4_6
Q4_7 0.377
Q4_8 0.857
Q4_9 0.653
Q4_10 0.767
Q4_11 0.626
Q4_12 0.392 0.325 0.428
Q4_13 0.420 0.598
Q4_14 0.369 0.446
Q4_15 0.618
Q4_16 0.567
Q4_17 0.666
Q4_18 0.869
Q4_19 0.628
Q5_1 0.370 0.334
Q5_2 0.637
Q5_3 0.715 0.363
Q5_4 0.910
Q5_5 0.873
Q5_6 0.773
Q5_7 0.355 0.311
Q5_8 0.734
Q5_9 0.505
Q5_10 0.344
Q5_11
Q5_12 0.410
Q6_1 0.738
Q6_2 0.959
Q6_3 1.005
Q6_4 0.974
Q6_5
Q6_6 0.734
Q6_7 0.749
Q6_8 0.799
Q6_9 0.432 0.582
Q6_10
Q6_11 0.304 0.308
Q7_1 0.629
Q7_2 0.331 0.307
Q7_3 0.891
Q7_4 0.399 0.544 -0.326
Q7_5 0.507 0.378
Q7_6 0.573
Q7_7 0.928
Q7_8 0.484 0.328
Q7_9 0.821
Q7_10 0.880
Q7_11 0.589
Q7_12 0.610 0.323
Q7_13 0.707
Q7_14 0.777
Q7_15 0.815
PA1 PA6 PA2 PA4 PA5 PA3
SS loadings 8.393 6.097 5.277 5.044 4.466 2.648
Proportion Var 0.147 0.107 0.093 0.088 0.078 0.046
Cumulative Var 0.147 0.254 0.347 0.435 0.514 0.560
fit <- psych::fa(r = cov.dat, nfactors = 6, rotate = "Promax", fm = "pa", covar = T)
fit
Factor Analysis using method = pa
Call: psych::fa(r = cov.dat, nfactors = 6, rotate = "Promax", covar = T,
fm = "pa")
Unstandardized loadings (pattern matrix) based upon covariance matrix
PA1 PA4 PA3 PA5 PA2 PA6 h2 u2 H2 U2
Q4_1 0.68 0.01 -0.10 0.21 -0.06 -0.17 0.44 0.31 0.59 0.41
Q4_2 0.68 0.01 -0.10 0.12 -0.05 -0.07 0.43 0.24 0.64 0.36
Q4_3 0.67 0.00 -0.10 0.14 0.01 -0.15 0.41 0.28 0.60 0.40
Q4_4 0.60 0.00 -0.01 0.19 0.12 -0.25 0.44 0.22 0.67 0.33
Q4_5 0.48 0.08 0.02 0.17 -0.09 -0.01 0.41 0.37 0.52 0.48
Q4_6 0.26 0.26 0.14 0.10 0.13 -0.12 0.42 0.54 0.44 0.56
Q4_7 0.15 0.26 0.14 -0.09 0.33 -0.13 0.32 0.56 0.37 0.63
Q4_8 0.81 -0.07 0.03 -0.04 -0.05 -0.01 0.53 0.33 0.62 0.38
Q4_9 0.73 -0.11 -0.03 -0.08 0.12 0.10 0.50 0.52 0.49 0.51
Q4_10 0.56 -0.02 0.05 0.01 0.17 -0.15 0.35 0.27 0.56 0.44
Q4_11 0.64 -0.04 -0.01 0.00 0.09 0.14 0.56 0.36 0.61 0.39
Q4_12 0.52 -0.09 0.29 -0.28 0.07 0.36 0.61 0.49 0.55 0.45
Q4_13 0.48 -0.06 0.16 -0.16 -0.12 0.31 0.40 0.37 0.52 0.48
Q4_14 0.42 0.04 0.03 -0.12 0.07 0.33 0.44 0.36 0.55 0.45
Q4_15 0.63 0.07 -0.02 -0.04 -0.05 0.17 0.53 0.31 0.63 0.37
Q4_16 0.56 0.22 0.10 -0.05 -0.10 -0.03 0.47 0.42 0.53 0.47
Q4_17 0.68 -0.12 0.09 -0.01 0.02 0.04 0.47 0.46 0.51 0.49
Q4_18 0.73 0.03 -0.07 0.04 -0.05 -0.02 0.50 0.18 0.73 0.27
Q4_19 0.69 0.00 -0.02 -0.07 0.10 0.14 0.60 0.34 0.63 0.37
Q5_1 0.18 0.32 -0.21 0.21 -0.07 0.26 0.46 0.45 0.51 0.49
Q5_2 0.03 0.66 0.06 -0.04 0.04 0.06 0.56 0.51 0.52 0.48
Q5_3 0.06 0.72 -0.09 0.04 -0.21 0.26 0.68 0.41 0.62 0.38
Q5_4 -0.02 1.04 0.00 -0.17 0.20 -0.27 0.80 0.42 0.65 0.35
Q5_5 -0.03 0.96 -0.06 -0.11 0.18 -0.32 0.64 0.43 0.60 0.40
Q5_6 0.05 0.71 -0.01 0.03 0.02 -0.05 0.54 0.28 0.65 0.35
Q5_7 -0.01 0.31 0.25 -0.05 0.08 0.18 0.40 0.48 0.45 0.55
Q5_8 -0.09 0.76 0.04 0.09 0.04 0.02 0.67 0.44 0.60 0.40
Q5_9 0.05 0.46 0.06 0.28 -0.15 0.14 0.62 0.37 0.62 0.38
Q5_10 0.10 0.30 0.06 0.11 -0.01 0.04 0.28 0.42 0.39 0.61
Q5_11 0.11 0.16 -0.05 0.30 0.03 0.19 0.43 0.48 0.47 0.53
Q5_12 0.00 0.36 0.06 0.20 0.11 0.03 0.43 0.48 0.47 0.53
Q6_1 -0.02 -0.01 0.60 0.00 -0.11 0.10 0.39 0.32 0.55 0.45
Q6_2 -0.06 0.05 0.86 -0.01 -0.01 -0.11 0.59 0.24 0.71 0.29
Q6_3 -0.05 0.08 0.88 -0.11 0.02 -0.11 0.59 0.26 0.70 0.30
Q6_4 -0.02 0.03 0.86 -0.05 -0.01 -0.18 0.54 0.32 0.62 0.38
Q6_5 -0.03 -0.06 0.15 0.24 0.02 0.30 0.31 0.76 0.29 0.71
Q6_6 0.02 -0.09 0.56 0.19 -0.04 0.02 0.43 0.24 0.64 0.36
Q6_7 0.11 -0.14 0.59 0.07 0.02 0.12 0.52 0.24 0.68 0.32
Q6_8 -0.01 -0.18 0.64 0.18 -0.02 0.12 0.55 0.26 0.68 0.32
Q6_9 0.06 -0.28 -0.04 -0.08 0.33 0.90 0.74 0.75 0.49 0.51
Q6_10 -0.03 0.00 0.03 0.21 0.12 0.35 0.34 0.50 0.41 0.59
Q6_11 -0.01 0.11 0.22 0.08 0.24 0.26 0.52 0.42 0.55 0.45
Q7_1 -0.04 0.10 0.08 0.59 -0.01 0.06 0.54 0.28 0.66 0.34
Q7_2 0.01 0.10 0.09 0.28 0.24 0.01 0.38 0.35 0.52 0.48
Q7_3 -0.03 0.14 0.10 -0.15 0.79 0.04 0.66 0.36 0.65 0.35
Q7_4 -0.07 -0.05 0.16 0.57 0.36 -0.21 0.55 0.41 0.57 0.43
Q7_5 0.08 -0.12 0.00 0.41 0.40 0.10 0.58 0.32 0.64 0.36
Q7_6 0.10 -0.03 0.10 0.04 0.45 0.19 0.47 0.38 0.55 0.45
Q7_7 0.10 0.15 -0.09 -0.19 0.79 0.14 0.70 0.33 0.68 0.32
Q7_8 0.08 -0.06 -0.06 0.28 0.36 0.11 0.39 0.38 0.50 0.50
Q7_9 0.06 -0.03 -0.05 0.86 -0.08 -0.02 0.63 0.35 0.64 0.36
Q7_10 0.14 -0.11 0.07 0.85 -0.14 -0.11 0.61 0.28 0.68 0.32
Q7_11 0.11 -0.07 -0.05 0.50 0.22 -0.06 0.39 0.31 0.56 0.44
Q7_12 -0.05 -0.01 -0.13 0.12 0.47 0.36 0.47 0.58 0.45 0.55
Q7_13 -0.12 -0.10 -0.16 -0.12 0.53 0.46 0.31 0.67 0.31 0.69
Q7_14 -0.07 0.21 -0.07 -0.13 0.64 0.09 0.45 0.53 0.46 0.54
Q7_15 0.06 -0.05 -0.01 0.76 -0.09 -0.04 0.47 0.35 0.57 0.43
PA1 PA4 PA3 PA5 PA2 PA6
SS loadings 7.76 5.12 4.31 4.38 4.13 2.74
Proportion Var 0.15 0.10 0.08 0.09 0.08 0.05
Cumulative Var 0.15 0.25 0.34 0.42 0.51 0.56
Proportion Explained 0.27 0.18 0.15 0.15 0.15 0.10
Cumulative Proportion 0.27 0.45 0.60 0.76 0.90 1.00
Standardized loadings (pattern matrix)
item PA1 PA4 PA3 PA5 PA2 PA6 h2 u2
Q4_1 1 0.79 0.01 -0.12 0.24 -0.07 -0.20 0.59 0.41
Q4_2 2 0.83 0.01 -0.12 0.14 -0.06 -0.09 0.64 0.36
Q4_3 3 0.81 0.00 -0.12 0.17 0.01 -0.19 0.60 0.40
Q4_4 4 0.73 -0.01 -0.02 0.23 0.15 -0.31 0.67 0.33
Q4_5 5 0.55 0.09 0.02 0.19 -0.11 -0.01 0.52 0.48
Q4_6 6 0.27 0.27 0.14 0.10 0.14 -0.12 0.44 0.56
Q4_7 7 0.16 0.28 0.15 -0.09 0.35 -0.13 0.37 0.63
Q4_8 8 0.87 -0.08 0.04 -0.04 -0.05 -0.01 0.62 0.38
Q4_9 9 0.72 -0.11 -0.03 -0.08 0.12 0.10 0.49 0.51
Q4_10 10 0.71 -0.02 0.06 0.01 0.22 -0.19 0.56 0.44
Q4_11 11 0.67 -0.04 -0.01 -0.01 0.09 0.14 0.61 0.39
Q4_12 12 0.50 -0.08 0.28 -0.27 0.06 0.34 0.55 0.45
Q4_13 13 0.54 -0.07 0.18 -0.18 -0.14 0.35 0.52 0.48
Q4_14 14 0.46 0.05 0.03 -0.13 0.07 0.37 0.55 0.45
Q4_15 15 0.68 0.08 -0.02 -0.05 -0.06 0.18 0.63 0.37
Q4_16 16 0.60 0.24 0.11 -0.06 -0.11 -0.04 0.53 0.47
Q4_17 17 0.70 -0.12 0.09 -0.01 0.02 0.05 0.51 0.49
Q4_18 18 0.88 0.04 -0.08 0.05 -0.07 -0.02 0.73 0.27
Q4_19 19 0.71 0.00 -0.02 -0.07 0.10 0.15 0.63 0.37
Q5_1 20 0.19 0.34 -0.22 0.22 -0.08 0.27 0.51 0.49
Q5_2 21 0.03 0.64 0.06 -0.04 0.04 0.06 0.52 0.48
Q5_3 22 0.06 0.69 -0.09 0.04 -0.20 0.24 0.62 0.38
Q5_4 23 -0.02 0.94 0.00 -0.15 0.18 -0.24 0.65 0.35
Q5_5 24 -0.03 0.92 -0.06 -0.11 0.17 -0.31 0.60 0.40
Q5_6 25 0.05 0.78 -0.01 0.03 0.02 -0.05 0.65 0.35
Q5_7 26 -0.01 0.33 0.27 -0.05 0.08 0.20 0.45 0.55
Q5_8 27 -0.09 0.72 0.04 0.08 0.03 0.02 0.60 0.40
Q5_9 28 0.05 0.46 0.06 0.28 -0.15 0.14 0.62 0.38
Q5_10 29 0.12 0.36 0.07 0.13 -0.01 0.05 0.39 0.61
Q5_11 30 0.11 0.17 -0.06 0.32 0.03 0.20 0.47 0.53
Q5_12 31 0.00 0.38 0.07 0.21 0.12 0.03 0.47 0.53
Q6_1 32 -0.02 -0.01 0.71 0.00 -0.13 0.11 0.55 0.45
Q6_2 33 -0.07 0.05 0.94 -0.01 -0.01 -0.12 0.71 0.29
Q6_3 34 -0.05 0.08 0.95 -0.12 0.02 -0.12 0.70 0.30
Q6_4 35 -0.02 0.03 0.93 -0.05 -0.01 -0.19 0.62 0.38
Q6_5 36 -0.03 -0.06 0.14 0.24 0.02 0.29 0.29 0.71
Q6_6 37 0.03 -0.11 0.68 0.23 -0.05 0.03 0.64 0.36
Q6_7 38 0.13 -0.16 0.67 0.08 0.02 0.13 0.68 0.32
Q6_8 39 -0.01 -0.20 0.71 0.20 -0.03 0.13 0.68 0.32
Q6_9 40 0.05 -0.23 -0.03 -0.06 0.27 0.74 0.49 0.51
Q6_10 41 -0.03 0.00 0.03 0.23 0.13 0.38 0.41 0.59
Q6_11 42 -0.01 0.12 0.22 0.09 0.25 0.27 0.55 0.45
Q7_1 43 -0.04 0.11 0.09 0.65 -0.01 0.07 0.66 0.34
Q7_2 44 0.02 0.11 0.11 0.33 0.29 0.01 0.52 0.48
Q7_3 45 -0.03 0.14 0.10 -0.15 0.78 0.04 0.65 0.35
Q7_4 46 -0.07 -0.05 0.16 0.58 0.36 -0.21 0.57 0.43
Q7_5 47 0.09 -0.12 0.00 0.43 0.43 0.10 0.64 0.36
Q7_6 48 0.11 -0.04 0.11 0.04 0.49 0.21 0.55 0.45
Q7_7 49 0.10 0.15 -0.09 -0.19 0.78 0.14 0.68 0.32
Q7_8 50 0.09 -0.07 -0.07 0.32 0.41 0.13 0.50 0.50
Q7_9 51 0.06 -0.03 -0.05 0.87 -0.08 -0.02 0.64 0.36
Q7_10 52 0.15 -0.11 0.08 0.90 -0.15 -0.12 0.68 0.32
Q7_11 53 0.13 -0.08 -0.06 0.60 0.26 -0.07 0.56 0.44
Q7_12 54 -0.04 -0.01 -0.13 0.12 0.46 0.35 0.45 0.55
Q7_13 55 -0.12 -0.11 -0.16 -0.12 0.53 0.47 0.31 0.69
Q7_14 56 -0.07 0.21 -0.07 -0.13 0.65 0.10 0.46 0.54
Q7_15 57 0.07 -0.05 -0.02 0.84 -0.10 -0.04 0.57 0.43
PA1 PA4 PA3 PA5 PA2 PA6
SS loadings 8.71 5.75 4.84 4.92 4.64 3.08
Proportion Var 0.15 0.10 0.08 0.09 0.08 0.05
Cumulative Var 0.15 0.25 0.34 0.42 0.51 0.56
Cum. factor Var 0.27 0.45 0.60 0.76 0.90 1.00
With factor correlations of
PA1 PA4 PA3 PA5 PA2 PA6
PA1 1.00 0.65 0.59 0.73 0.45 0.62
PA4 0.65 1.00 0.55 0.72 0.51 0.61
PA3 0.59 0.55 1.00 0.65 0.31 0.64
PA5 0.73 0.72 0.65 1.00 0.60 0.69
PA2 0.45 0.51 0.31 0.60 1.00 0.35
PA6 0.62 0.61 0.64 0.69 0.35 1.00
Mean item complexity = 1.7
Test of the hypothesis that 6 factors are sufficient.
The degrees of freedom for the null model are 1596 and the objective function was 46.33
The degrees of freedom for the model are 1269 and the objective function was 8.78
The root mean square of the residuals (RMSR) is 0.03
The df corrected root mean square of the residuals is 0.03
Fit based upon off diagonal values = 0.99
Measures of factor score adequacy
PA1 PA4 PA3 PA5 PA2 PA6
Correlation of (regression) scores with factors 0.98 0.97 0.97 0.97 0.95 0.93
Multiple R square of scores with factors 0.96 0.93 0.94 0.94 0.90 0.86
Minimum correlation of possible factor scores 0.92 0.86 0.88 0.87 0.80 0.72
print(fit$loadings, cutoff=0.3)
Loadings:
PA1 PA4 PA3 PA5 PA2 PA6
Q4_1 0.684
Q4_2 0.678
Q4_3 0.674
Q4_4 0.599
Q4_5 0.484
Q4_6
Q4_7 0.331
Q4_8 0.805
Q4_9 0.726
Q4_10 0.561
Q4_11 0.644
Q4_12 0.523 0.358
Q4_13 0.477 0.308
Q4_14 0.416 0.331
Q4_15 0.628
Q4_16 0.562
Q4_17 0.677
Q4_18 0.727
Q4_19 0.690
Q5_1 0.321
Q5_2 0.664
Q5_3 0.719
Q5_4 1.035
Q5_5 0.956 -0.317
Q5_6 0.708
Q5_7 0.309
Q5_8 0.760
Q5_9 0.456
Q5_10
Q5_11 0.305
Q5_12 0.364
Q6_1 0.601
Q6_2 0.856
Q6_3 0.883
Q6_4 0.859
Q6_5
Q6_6 0.557
Q6_7 0.587
Q6_8 0.643
Q6_9 0.334 0.899
Q6_10 0.347
Q6_11
Q7_1 0.588
Q7_2
Q7_3 0.789
Q7_4 0.572 0.357
Q7_5 0.405 0.403
Q7_6 0.450
Q7_7 0.789
Q7_8 0.357
Q7_9 0.860
Q7_10 0.848
Q7_11 0.504
Q7_12 0.472 0.357
Q7_13 0.528 0.461
Q7_14 0.639
Q7_15 0.757
PA1 PA4 PA3 PA5 PA2 PA6
SS loadings 7.021 5.244 4.229 4.209 3.544 2.665
Proportion Var 0.123 0.092 0.074 0.074 0.062 0.047
Cumulative Var 0.123 0.215 0.289 0.363 0.425 0.472
We selected the following items based on these results:
Effective Learning (Q4) | Student Centered (Q5) | Interactive (Q6) | Engagement (Q7) |
---|---|---|---|
Q4-1 | Q5-1 | Q6-1 | Q7-2 |
Q4-2 | Q5-2 | Q6-2 | Q7-4 |
Q4-3 | Q5-3 | Q6-3 | Q7-5 |
Q4-4 | Q5-4 | Q6-4 | Q7-7 |
Q4-5 | Q5-5 | Q6-5 | Q7-8 |
Q4-8 | Q5-6 | Q6-6 | Q7-12 |
Q4-9 | Q5-8 | Q6-7 | Q7-13 |
Q4-10 | Q5-12 | Q6-8 | Q7-14 |
Q4-11 | Q6-12 | ||
Q4-15 | |||
Q4-16 | |||
Q4-17 | |||
Q4-18 | |||
Q4-19 |
For the item stems, please see the document here.
# item analysis
fit <- psychometric::item.exam(dat[, paste0("Q4_",c(1:5,8:11, 15:19))])
kable(fit[,c(1:4,7:8)], format="html", digits=3) %>%
kable_styling(full_width = T)%>%
scroll_box(width="100%")
Sample.SD | Item.total | Item.Tot.woi | Difficulty | Item.Reliab | Item.Rel.woi | |
---|---|---|---|---|---|---|
Q4_1 | 0.866 | 0.767 | 0.726 | 2.460 | 0.663 | 0.628 |
Q4_2 | 0.819 | 0.801 | 0.767 | 2.305 | 0.655 | 0.628 |
Q4_3 | 0.834 | 0.781 | 0.744 | 2.537 | 0.651 | 0.620 |
Q4_4 | 0.816 | 0.786 | 0.750 | 2.640 | 0.640 | 0.611 |
Q4_5 | 0.880 | 0.723 | 0.675 | 2.320 | 0.636 | 0.594 |
Q4_8 | 0.927 | 0.794 | 0.754 | 2.287 | 0.735 | 0.698 |
Q4_9 | 1.007 | 0.719 | 0.662 | 2.463 | 0.723 | 0.666 |
Q4_10 | 0.789 | 0.745 | 0.705 | 2.582 | 0.587 | 0.556 |
Q4_11 | 0.955 | 0.792 | 0.750 | 2.500 | 0.755 | 0.715 |
Q4_15 | 0.917 | 0.793 | 0.753 | 2.375 | 0.726 | 0.690 |
Q4_16 | 0.941 | 0.732 | 0.681 | 2.457 | 0.687 | 0.640 |
Q4_17 | 0.964 | 0.734 | 0.682 | 2.198 | 0.707 | 0.657 |
Q4_18 | 0.823 | 0.851 | 0.825 | 2.360 | 0.700 | 0.678 |
Q4_19 | 0.970 | 0.800 | 0.759 | 2.543 | 0.774 | 0.735 |
# post reliability
psych::alpha(dat[, paste0("Q4_",c(1:5,8:11, 15:19))])
Reliability analysis
Call: psych::alpha(x = dat[, paste0("Q4_", c(1:5, 8:11, 15:19))])
raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
0.95 0.95 0.95 0.57 18 0.0043 2.4 0.69 0.56
lower alpha upper 95% confidence boundaries
0.94 0.95 0.96
Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
Q4_1 0.94 0.94 0.95 0.57 17 0.0046 0.0044 0.56
Q4_2 0.94 0.94 0.95 0.56 17 0.0047 0.0045 0.56
Q4_3 0.94 0.94 0.95 0.56 17 0.0046 0.0046 0.56
Q4_4 0.94 0.94 0.95 0.56 17 0.0047 0.0045 0.56
Q4_5 0.94 0.95 0.95 0.57 17 0.0045 0.0045 0.57
Q4_8 0.94 0.94 0.95 0.56 17 0.0047 0.0050 0.55
Q4_9 0.95 0.95 0.95 0.58 18 0.0045 0.0039 0.57
Q4_10 0.94 0.94 0.95 0.57 17 0.0046 0.0048 0.56
Q4_11 0.94 0.94 0.95 0.56 17 0.0047 0.0050 0.55
Q4_15 0.94 0.94 0.95 0.56 17 0.0047 0.0049 0.56
Q4_16 0.94 0.95 0.95 0.57 17 0.0045 0.0043 0.57
Q4_17 0.94 0.95 0.95 0.57 17 0.0045 0.0047 0.57
Q4_18 0.94 0.94 0.95 0.56 16 0.0048 0.0041 0.55
Q4_19 0.94 0.94 0.95 0.56 17 0.0047 0.0047 0.56
Item statistics
n raw.r std.r r.cor r.drop mean sd
Q4_1 328 0.77 0.77 0.75 0.73 2.5 0.87
Q4_2 328 0.80 0.81 0.79 0.77 2.3 0.82
Q4_3 328 0.78 0.79 0.77 0.74 2.5 0.83
Q4_4 328 0.79 0.79 0.78 0.75 2.6 0.82
Q4_5 328 0.72 0.73 0.70 0.68 2.3 0.88
Q4_8 328 0.79 0.79 0.77 0.75 2.3 0.93
Q4_9 328 0.72 0.71 0.69 0.66 2.5 1.01
Q4_10 328 0.75 0.75 0.73 0.71 2.6 0.79
Q4_11 328 0.79 0.79 0.77 0.75 2.5 0.95
Q4_15 328 0.79 0.79 0.77 0.75 2.4 0.92
Q4_16 328 0.73 0.73 0.71 0.68 2.5 0.94
Q4_17 328 0.73 0.73 0.70 0.68 2.2 0.96
Q4_18 328 0.85 0.85 0.85 0.82 2.4 0.82
Q4_19 328 0.80 0.79 0.78 0.76 2.5 0.97
Non missing response frequency for each item
1 2 3 4 5 miss
Q4_1 0.13 0.38 0.39 0.09 0.01 0
Q4_2 0.15 0.47 0.32 0.05 0.01 0
Q4_3 0.10 0.37 0.44 0.08 0.02 0
Q4_4 0.09 0.28 0.54 0.08 0.02 0
Q4_5 0.16 0.47 0.28 0.08 0.01 0
Q4_8 0.20 0.43 0.28 0.07 0.02 0
Q4_9 0.15 0.42 0.27 0.12 0.04 0
Q4_10 0.09 0.30 0.54 0.04 0.02 0
Q4_11 0.16 0.34 0.38 0.10 0.02 0
Q4_15 0.16 0.41 0.33 0.07 0.02 0
Q4_16 0.17 0.33 0.40 0.08 0.02 0
Q4_17 0.26 0.39 0.25 0.08 0.02 0
Q4_18 0.13 0.47 0.34 0.06 0.01 0
Q4_19 0.14 0.35 0.39 0.08 0.04 0
# item analysis
fit <- psychometric::item.exam(dat[, paste0("Q5_",c(1:6, 8, 12))])
kable(fit[,c(1:4,7:8)], format="html", digits=3) %>%
kable_styling(full_width = T)%>%
scroll_box(width="100%")
Sample.SD | Item.total | Item.Tot.woi | Difficulty | Item.Reliab | Item.Rel.woi | |
---|---|---|---|---|---|---|
Q5_1 | 0.951 | 0.686 | 0.591 | 2.637 | 0.652 | 0.561 |
Q5_2 | 1.035 | 0.778 | 0.697 | 2.954 | 0.804 | 0.720 |
Q5_3 | 1.046 | 0.790 | 0.711 | 2.662 | 0.825 | 0.743 |
Q5_4 | 1.106 | 0.785 | 0.700 | 3.500 | 0.867 | 0.772 |
Q5_5 | 1.034 | 0.736 | 0.643 | 3.530 | 0.760 | 0.664 |
Q5_6 | 0.906 | 0.827 | 0.771 | 2.927 | 0.748 | 0.697 |
Q5_8 | 1.055 | 0.792 | 0.713 | 2.905 | 0.835 | 0.752 |
Q5_12 | 0.952 | 0.701 | 0.608 | 2.881 | 0.666 | 0.578 |
# post reliability
psych::alpha(dat[, paste0("Q5_",c(1:6, 8, 12))])
Reliability analysis
Call: psych::alpha(x = dat[, paste0("Q5_", c(1:6, 8, 12))])
raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
0.9 0.9 0.9 0.52 8.7 0.0087 3 0.77 0.51
lower alpha upper 95% confidence boundaries
0.88 0.9 0.91
Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
Q5_1 0.89 0.89 0.90 0.54 8.3 0.0093 0.0088 0.53
Q5_2 0.88 0.88 0.89 0.52 7.5 0.0100 0.0106 0.52
Q5_3 0.88 0.88 0.88 0.51 7.4 0.0101 0.0100 0.51
Q5_4 0.88 0.88 0.87 0.52 7.5 0.0100 0.0075 0.51
Q5_5 0.89 0.89 0.88 0.53 7.9 0.0095 0.0048 0.52
Q5_6 0.88 0.88 0.88 0.50 7.0 0.0105 0.0096 0.50
Q5_8 0.88 0.88 0.89 0.51 7.4 0.0102 0.0109 0.51
Q5_12 0.89 0.89 0.90 0.54 8.1 0.0094 0.0107 0.54
Item statistics
n raw.r std.r r.cor r.drop mean sd
Q5_1 328 0.69 0.69 0.63 0.59 2.6 0.95
Q5_2 328 0.78 0.78 0.74 0.70 3.0 1.04
Q5_3 328 0.79 0.79 0.76 0.71 2.7 1.05
Q5_4 328 0.79 0.78 0.76 0.70 3.5 1.11
Q5_5 328 0.74 0.73 0.71 0.64 3.5 1.03
Q5_6 328 0.83 0.83 0.81 0.77 2.9 0.91
Q5_8 328 0.79 0.79 0.75 0.71 2.9 1.06
Q5_12 328 0.70 0.71 0.64 0.61 2.9 0.95
Non missing response frequency for each item
1 2 3 4 5 miss
Q5_1 0.12 0.32 0.40 0.14 0.03 0
Q5_2 0.10 0.20 0.38 0.27 0.05 0
Q5_3 0.15 0.29 0.35 0.17 0.04 0
Q5_4 0.08 0.11 0.21 0.46 0.15 0
Q5_5 0.05 0.12 0.21 0.48 0.14 0
Q5_6 0.09 0.15 0.52 0.21 0.02 0
Q5_8 0.12 0.19 0.39 0.24 0.05 0
Q5_12 0.10 0.17 0.50 0.19 0.04 0
# item analysis
fit <- psychometric::item.exam(dat[, paste0("Q6_",c(1:8, 11))])
kable(fit[,c(1:4,7:8)], format="html", digits=3) %>%
kable_styling(full_width = T)%>%
scroll_box(width="100%")
Sample.SD | Item.total | Item.Tot.woi | Difficulty | Item.Reliab | Item.Rel.woi | |
---|---|---|---|---|---|---|
Q6_1 | 0.844 | 0.757 | 0.690 | 1.701 | 0.638 | 0.581 |
Q6_2 | 0.912 | 0.828 | 0.773 | 2.079 | 0.754 | 0.703 |
Q6_3 | 0.924 | 0.824 | 0.766 | 1.930 | 0.760 | 0.707 |
Q6_4 | 0.927 | 0.774 | 0.703 | 2.076 | 0.716 | 0.651 |
Q6_5 | 1.033 | 0.572 | 0.444 | 2.351 | 0.589 | 0.458 |
Q6_6 | 0.820 | 0.818 | 0.766 | 1.832 | 0.669 | 0.627 |
Q6_7 | 0.875 | 0.841 | 0.791 | 2.162 | 0.735 | 0.691 |
Q6_8 | 0.903 | 0.827 | 0.772 | 2.113 | 0.746 | 0.697 |
Q6_11 | 0.970 | 0.659 | 0.557 | 2.814 | 0.638 | 0.539 |
# post reliability
psych::alpha(dat[, paste0("Q6_",c(1:8, 11))])
Reliability analysis
Call: psych::alpha(x = dat[, paste0("Q6_", c(1:8, 11))])
raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
0.91 0.91 0.92 0.54 10 0.0076 2.1 0.7 0.57
lower alpha upper 95% confidence boundaries
0.89 0.91 0.92
Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
Q6_1 0.90 0.90 0.91 0.54 9.3 0.0086 0.019 0.57
Q6_2 0.89 0.90 0.90 0.52 8.7 0.0091 0.018 0.56
Q6_3 0.89 0.90 0.90 0.52 8.7 0.0091 0.019 0.56
Q6_4 0.90 0.90 0.90 0.53 9.2 0.0087 0.017 0.56
Q6_5 0.92 0.92 0.92 0.59 11.4 0.0069 0.010 0.59
Q6_6 0.89 0.90 0.90 0.52 8.8 0.0090 0.021 0.56
Q6_7 0.89 0.90 0.90 0.52 8.6 0.0092 0.020 0.56
Q6_8 0.89 0.90 0.90 0.52 8.7 0.0091 0.020 0.56
Q6_11 0.91 0.91 0.92 0.56 10.4 0.0077 0.019 0.59
Item statistics
n raw.r std.r r.cor r.drop mean sd
Q6_1 328 0.76 0.76 0.73 0.69 1.7 0.84
Q6_2 328 0.83 0.83 0.82 0.77 2.1 0.91
Q6_3 328 0.82 0.83 0.81 0.77 1.9 0.92
Q6_4 328 0.77 0.78 0.75 0.70 2.1 0.93
Q6_5 328 0.57 0.56 0.47 0.44 2.4 1.03
Q6_6 328 0.82 0.82 0.80 0.77 1.8 0.82
Q6_7 328 0.84 0.84 0.83 0.79 2.2 0.88
Q6_8 328 0.83 0.83 0.81 0.77 2.1 0.90
Q6_11 328 0.66 0.65 0.59 0.56 2.8 0.97
Non missing response frequency for each item
1 2 3 4 5 miss
Q6_1 0.49 0.36 0.09 0.05 0.00 0
Q6_2 0.27 0.47 0.17 0.07 0.01 0
Q6_3 0.36 0.45 0.13 0.05 0.02 0
Q6_4 0.29 0.43 0.20 0.06 0.01 0
Q6_5 0.19 0.46 0.21 0.10 0.04 0
Q6_6 0.37 0.48 0.11 0.03 0.01 0
Q6_7 0.21 0.50 0.20 0.07 0.01 0
Q6_8 0.25 0.47 0.20 0.07 0.01 0
Q6_11 0.11 0.21 0.49 0.14 0.05 0
# item analysis
fit <- psychometric::item.exam(dat[, paste0("Q7_",c(2, 4:5, 7:8, 12:14))])
kable(fit[,c(1:4,7:8)], format="html", digits=3) %>%
kable_styling(full_width = T)%>%
scroll_box(width="100%")
Sample.SD | Item.total | Item.Tot.woi | Difficulty | Item.Reliab | Item.Rel.woi | |
---|---|---|---|---|---|---|
Q7_2 | 0.857 | 0.701 | 0.607 | 2.692 | 0.599 | 0.519 |
Q7_4 | 0.980 | 0.710 | 0.602 | 2.841 | 0.694 | 0.589 |
Q7_5 | 0.948 | 0.798 | 0.720 | 2.875 | 0.756 | 0.682 |
Q7_7 | 1.014 | 0.789 | 0.701 | 3.652 | 0.799 | 0.710 |
Q7_8 | 0.877 | 0.736 | 0.648 | 2.814 | 0.644 | 0.567 |
Q7_12 | 1.023 | 0.717 | 0.605 | 3.390 | 0.732 | 0.618 |
Q7_13 | 0.989 | 0.571 | 0.430 | 3.579 | 0.564 | 0.425 |
Q7_14 | 0.986 | 0.694 | 0.581 | 3.610 | 0.684 | 0.573 |
# post reliability
psych::alpha(dat[, paste0("Q7_",c(2, 4:5, 7:8, 12:14))])
Reliability analysis
Call: psych::alpha(x = dat[, paste0("Q7_", c(2, 4:5, 7:8, 12:14))])
raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
0.86 0.86 0.87 0.44 6.3 0.012 3.2 0.69 0.45
lower alpha upper 95% confidence boundaries
0.84 0.86 0.88
Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
Q7_2 0.85 0.85 0.85 0.44 5.5 0.013 0.0148 0.45
Q7_4 0.85 0.85 0.84 0.44 5.5 0.013 0.0113 0.45
Q7_5 0.83 0.83 0.83 0.42 5.0 0.014 0.0124 0.42
Q7_7 0.83 0.84 0.84 0.42 5.1 0.014 0.0164 0.41
Q7_8 0.84 0.84 0.84 0.43 5.3 0.013 0.0146 0.45
Q7_12 0.85 0.85 0.85 0.44 5.6 0.013 0.0188 0.45
Q7_13 0.87 0.87 0.86 0.48 6.5 0.011 0.0083 0.47
Q7_14 0.85 0.85 0.85 0.45 5.7 0.013 0.0185 0.47
Item statistics
n raw.r std.r r.cor r.drop mean sd
Q7_2 328 0.70 0.71 0.66 0.61 2.7 0.86
Q7_4 328 0.71 0.71 0.68 0.60 2.8 0.98
Q7_5 328 0.80 0.80 0.79 0.72 2.9 0.95
Q7_7 328 0.79 0.78 0.75 0.70 3.7 1.01
Q7_8 328 0.74 0.75 0.70 0.65 2.8 0.88
Q7_12 328 0.72 0.71 0.65 0.61 3.4 1.02
Q7_13 328 0.57 0.56 0.47 0.43 3.6 0.99
Q7_14 328 0.69 0.69 0.62 0.58 3.6 0.99
Non missing response frequency for each item
1 2 3 4 5 miss
Q7_2 0.11 0.21 0.57 0.09 0.02 0
Q7_4 0.10 0.21 0.47 0.17 0.05 0
Q7_5 0.10 0.18 0.51 0.17 0.04 0
Q7_7 0.05 0.09 0.17 0.53 0.16 0
Q7_8 0.10 0.17 0.55 0.15 0.02 0
Q7_12 0.07 0.09 0.32 0.43 0.10 0
Q7_13 0.02 0.11 0.32 0.36 0.19 0
Q7_14 0.05 0.08 0.24 0.48 0.15 0
sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] xtable_1.8-4 kableExtra_1.1.0 readxl_1.3.1 nFactors_2.4.1
[5] lattice_0.20-41 psych_2.0.7 psychometric_2.2 multilevel_2.6
[9] MASS_7.3-51.6 nlme_3.1-148 mvtnorm_1.1-1 ggcorrplot_0.1.3
[13] naniar_0.6.0 simsem_0.5-15 MIIVsem_0.5.5 lavaanPlot_0.5.1
[17] semTools_0.5-3 lavaan_0.6-7 data.table_1.13.0 patchwork_1.0.1
[21] forcats_0.5.0 stringr_1.4.0 dplyr_1.0.1 purrr_0.3.4
[25] readr_1.3.1 tidyr_1.1.1 tibble_3.0.3 ggplot2_3.3.2
[29] tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] fs_1.5.0 lubridate_1.7.9 webshot_0.5.2 RColorBrewer_1.1-2
[5] httr_1.4.2 rprojroot_1.3-2 tools_4.0.2 backports_1.1.7
[9] R6_2.4.1 DBI_1.1.0 colorspace_1.4-1 withr_2.2.0
[13] tidyselect_1.1.0 mnormt_2.0.2 emmeans_1.4.8 compiler_4.0.2
[17] git2r_0.27.1 cli_2.0.2 rvest_0.3.6 xml2_1.3.2
[21] sandwich_2.5-1 scales_1.1.1 digest_0.6.25 pbivnorm_0.6.0
[25] rmarkdown_2.5 pkgconfig_2.0.3 htmltools_0.5.0 highr_0.8
[29] dbplyr_1.4.4 htmlwidgets_1.5.1 rlang_0.4.7 rstudioapi_0.11
[33] visNetwork_2.0.9 generics_0.0.2 zoo_1.8-8 jsonlite_1.7.0
[37] magrittr_1.5 Matrix_1.2-18 Rcpp_1.0.5 munsell_0.5.0
[41] fansi_0.4.1 visdat_0.5.3 lifecycle_0.2.0 stringi_1.4.6
[45] multcomp_1.4-13 whisker_0.4 yaml_2.2.1 grid_4.0.2
[49] blob_1.2.1 parallel_4.0.2 promises_1.1.1 crayon_1.3.4
[53] haven_2.3.1 splines_4.0.2 hms_0.5.3 tmvnsim_1.0-2
[57] knitr_1.29 pillar_1.4.6 estimability_1.3 codetools_0.2-16
[61] stats4_4.0.2 reprex_0.3.0 glue_1.4.1 evaluate_0.14
[65] modelr_0.1.8 vctrs_0.3.2 httpuv_1.5.4 cellranger_1.1.0
[69] gtable_0.3.0 assertthat_0.2.1 xfun_0.19 broom_0.7.0
[73] coda_0.19-3 later_1.1.0.1 viridisLite_0.3.0 survival_3.2-3
[77] DiagrammeR_1.0.6.1 TH.data_1.0-10 ellipsis_0.3.1