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source("code/load_packages.R")-- Attaching packages -------------------------------- tidyverse 1.3.0 --v ggplot2 3.3.2 v purrr 0.3.4
v tibble 3.0.3 v dplyr 1.0.1
v tidyr 1.1.1 v stringr 1.4.0
v readr 1.3.1 v forcats 0.5.0-- Conflicts ----------------------------------- tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()
Attaching package: 'data.table'The following objects are masked from 'package:dplyr':
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transposeThis is lavaan 0.6-7lavaan is BETA software! Please report any bugs. ###############################################################################This is semTools 0.5-3All users of R (or SEM) are invited to submit functions or ideas for functions.###############################################################################
Attaching package: 'semTools'The following object is masked from 'package:readr':
clipboardWarning: package 'MIIVsem' was built under R version 4.0.3This is MIIVsem 0.5.5MIIVsem is BETA software! Please report any bugs. #################################################################This is simsem 0.5-15simsem is BETA software! Please report any bugs.simsem was first developed at the University of Kansas Center forResearch Methods and Data Analysis, under NSF Grant 1053160.#################################################################
Attaching package: 'simsem'The following object is masked from 'package:lavaan':
inspectWarning: package 'naniar' was built under R version 4.0.3Warning: package 'ggcorrplot' was built under R version 4.0.3Loading required package: multilevelLoading required package: nlme
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%+%, alphaWarning: package 'nFactors' was built under R version 4.0.3Loading required package: lattice
Attaching package: 'nFactors'The following object is masked from 'package:lattice':
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group_rowsmydata <- read.table("data/data-2020-11-16/pools_data_split2_2020_11_16.txt", sep="\t", header=T)
# transform responses to (-2, 2) scale
mydata[, 7:63] <- apply(mydata[,7:63], 2, function(x){x-3})psych::describe(
mydata[, c(paste0("Q4_",c(1:5,8:11, 15:19)),
paste0("Q5_",c(1:6, 8, 12)),
paste0("Q6_",c(1:8, 11)),
paste0("Q7_",c(2, 4:5, 7:8, 12:14)))]
) vars n mean sd median trimmed mad min max range skew kurtosis se
Q4_1 1 312 -0.62 0.85 -1.0 -0.63 1.48 -2 2 4 0.28 0.06 0.05
Q4_2 2 312 -0.80 0.78 -1.0 -0.82 0.00 -2 2 4 0.64 1.07 0.04
Q4_3 3 312 -0.54 0.85 -1.0 -0.54 1.48 -2 2 4 0.35 0.47 0.05
Q4_4 4 312 -0.47 0.85 0.0 -0.46 1.48 -2 2 4 -0.01 0.12 0.05
Q4_5 5 312 -0.75 0.87 -1.0 -0.81 1.48 -2 2 4 0.61 0.32 0.05
Q4_8 6 312 -0.81 0.85 -1.0 -0.86 1.48 -2 2 4 0.50 0.16 0.05
Q4_9 7 312 -0.61 0.97 -1.0 -0.66 1.48 -2 2 4 0.45 -0.29 0.05
Q4_10 8 312 -0.46 0.80 0.0 -0.41 0.00 -2 2 4 -0.19 0.30 0.05
Q4_11 9 312 -0.52 0.95 -1.0 -0.56 1.48 -2 2 4 0.26 -0.26 0.05
Q4_15 10 312 -0.71 0.88 -1.0 -0.75 1.48 -2 2 4 0.34 -0.32 0.05
Q4_16 11 312 -0.67 0.93 -1.0 -0.72 1.48 -2 2 4 0.23 -0.50 0.05
Q4_17 12 312 -0.90 0.93 -1.0 -0.99 1.48 -2 2 4 0.53 -0.47 0.05
Q4_18 13 312 -0.72 0.79 -1.0 -0.74 0.00 -2 2 4 0.49 0.33 0.04
Q4_19 14 312 -0.51 0.97 -0.5 -0.54 0.74 -2 2 4 0.22 -0.38 0.06
Q5_1 15 312 -0.47 0.95 -1.0 -0.49 1.48 -2 2 4 0.19 -0.49 0.05
Q5_2 16 312 -0.04 1.01 0.0 0.01 1.48 -2 2 4 -0.20 -0.49 0.06
Q5_3 17 312 -0.41 1.04 0.0 -0.43 1.48 -2 2 4 0.26 -0.52 0.06
Q5_4 18 312 0.46 1.10 1.0 0.55 0.00 -2 2 4 -0.80 -0.15 0.06
Q5_5 19 312 0.45 1.06 1.0 0.52 0.00 -2 2 4 -0.78 -0.16 0.06
Q5_6 20 312 -0.15 0.92 0.0 -0.14 1.48 -2 2 4 0.03 -0.07 0.05
Q5_8 21 312 -0.16 1.07 0.0 -0.13 1.48 -2 2 4 -0.09 -0.66 0.06
Q5_12 22 312 -0.20 1.01 0.0 -0.18 1.48 -2 2 4 -0.10 -0.29 0.06
Q6_1 23 312 -1.32 0.86 -1.5 -1.48 0.74 -2 2 4 1.52 2.55 0.05
Q6_2 24 312 -0.96 0.91 -1.0 -1.07 0.00 -2 2 4 0.98 0.92 0.05
Q6_3 25 312 -1.01 0.92 -1.0 -1.13 1.48 -2 2 4 1.03 1.03 0.05
Q6_4 26 312 -0.89 0.94 -1.0 -0.99 1.48 -2 2 4 0.84 0.64 0.05
Q6_5 27 312 -0.61 1.10 -1.0 -0.69 1.48 -2 2 4 0.57 -0.45 0.06
Q6_6 28 312 -1.18 0.79 -1.0 -1.29 0.00 -2 2 4 1.08 1.68 0.04
Q6_7 29 312 -0.89 0.88 -1.0 -0.95 1.48 -2 2 4 0.61 0.19 0.05
Q6_8 30 312 -0.85 0.83 -1.0 -0.90 0.00 -2 2 4 0.70 0.77 0.05
Q6_11 31 312 -0.31 0.98 0.0 -0.30 1.48 -2 2 4 -0.11 -0.29 0.06
Q7_2 32 312 -0.35 0.89 0.0 -0.33 0.00 -2 2 4 -0.35 -0.09 0.05
Q7_4 33 312 -0.21 0.94 0.0 -0.18 1.48 -2 2 4 -0.07 -0.15 0.05
Q7_5 34 312 -0.21 0.94 0.0 -0.19 0.00 -2 2 4 -0.14 0.12 0.05
Q7_7 35 312 0.57 1.07 1.0 0.66 0.00 -2 2 4 -0.86 0.08 0.06
Q7_8 36 312 -0.19 0.94 0.0 -0.16 0.00 -2 2 4 -0.07 0.03 0.05
Q7_12 37 312 0.38 1.07 1.0 0.44 1.48 -2 2 4 -0.55 -0.17 0.06
Q7_13 38 312 0.49 1.11 1.0 0.56 1.48 -2 2 4 -0.50 -0.42 0.06
Q7_14 39 312 0.56 1.04 1.0 0.64 1.48 -2 2 4 -0.69 0.00 0.06mod1 <- "
EL =~ Q4_1 + Q4_2 + Q4_3 + Q4_4 + Q4_5 + Q4_8 + Q4_9 + Q4_10 + Q4_11 + Q4_15 + Q4_16 + Q4_17 + Q4_18 + Q4_19
SC =~ Q5_1 + Q5_2 + Q5_3 + Q5_4 + Q5_5 + Q5_6 + Q5_8 + Q5_12
IN =~ Q6_1 + Q6_2 + Q6_3 + Q6_4 + Q6_5 + Q6_6 + Q6_7 + Q6_8 + Q6_11
EN =~ Q7_2 + Q7_4 + Q7_5 + Q7_7 + Q7_8 + Q7_12 + Q7_13 + Q7_14
EL ~~ EL + SC + IN + EN
SC ~~ SC + IN + EN
IN ~~ IN + EN
EN ~~ EN
"
fit1 <- lavaan::cfa(mod1, data=mydata)
summary(fit1, standardized=T, fit.measures=T)lavaan 0.6-7 ended normally after 69 iterations
Estimator ML
Optimization method NLMINB
Number of free parameters 84
Number of observations 312
Model Test User Model:
Test statistic 2124.858
Degrees of freedom 696
P-value (Chi-square) 0.000
Model Test Baseline Model:
Test statistic 8846.565
Degrees of freedom 741
P-value 0.000
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.824
Tucker-Lewis Index (TLI) 0.812
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -13071.075
Loglikelihood unrestricted model (H1) -12008.646
Akaike (AIC) 26310.149
Bayesian (BIC) 26624.561
Sample-size adjusted Bayesian (BIC) 26358.142
Root Mean Square Error of Approximation:
RMSEA 0.081
90 Percent confidence interval - lower 0.077
90 Percent confidence interval - upper 0.085
P-value RMSEA <= 0.05 0.000
Standardized Root Mean Square Residual:
SRMR 0.080
Parameter Estimates:
Standard errors Standard
Information Expected
Information saturated (h1) model Structured
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EL =~
Q4_1 1.000 0.658 0.774
Q4_2 0.891 0.062 14.261 0.000 0.587 0.750
Q4_3 1.023 0.067 15.358 0.000 0.674 0.796
Q4_4 1.034 0.066 15.544 0.000 0.681 0.804
Q4_5 0.990 0.069 14.257 0.000 0.652 0.749
Q4_8 0.939 0.069 13.689 0.000 0.618 0.725
Q4_9 1.008 0.078 12.867 0.000 0.664 0.688
Q4_10 0.930 0.064 14.644 0.000 0.613 0.766
Q4_11 1.088 0.076 14.348 0.000 0.716 0.753
Q4_15 0.963 0.071 13.544 0.000 0.634 0.718
Q4_16 0.941 0.076 12.408 0.000 0.620 0.667
Q4_17 0.856 0.077 11.130 0.000 0.563 0.607
Q4_18 0.980 0.062 15.887 0.000 0.645 0.818
Q4_19 1.115 0.077 14.418 0.000 0.734 0.756
SC =~
Q5_1 1.000 0.547 0.575
Q5_2 1.144 0.130 8.792 0.000 0.625 0.619
Q5_3 1.250 0.136 9.170 0.000 0.684 0.657
Q5_4 1.593 0.154 10.326 0.000 0.871 0.792
Q5_5 1.548 0.149 10.387 0.000 0.846 0.800
Q5_6 1.310 0.128 10.225 0.000 0.716 0.779
Q5_8 1.527 0.149 10.234 0.000 0.835 0.780
Q5_12 1.111 0.129 8.603 0.000 0.607 0.600
IN =~
Q6_1 1.000 0.587 0.686
Q6_2 1.218 0.095 12.824 0.000 0.714 0.786
Q6_3 1.258 0.097 13.010 0.000 0.738 0.799
Q6_4 1.236 0.098 12.674 0.000 0.725 0.776
Q6_5 0.855 0.112 7.663 0.000 0.501 0.456
Q6_6 1.050 0.082 12.784 0.000 0.616 0.784
Q6_7 1.226 0.092 13.345 0.000 0.719 0.822
Q6_8 1.164 0.087 13.314 0.000 0.683 0.820
Q6_11 1.029 0.100 10.258 0.000 0.603 0.619
EN =~
Q7_2 1.000 0.654 0.737
Q7_4 0.926 0.084 11.058 0.000 0.605 0.643
Q7_5 1.077 0.083 12.945 0.000 0.704 0.747
Q7_7 1.146 0.094 12.134 0.000 0.749 0.702
Q7_8 1.103 0.083 13.372 0.000 0.721 0.771
Q7_12 1.083 0.095 11.449 0.000 0.708 0.665
Q7_13 0.635 0.100 6.365 0.000 0.415 0.376
Q7_14 1.017 0.093 10.969 0.000 0.665 0.638
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EL ~~
SC 0.205 0.032 6.505 0.000 0.571 0.571
IN 0.267 0.034 7.767 0.000 0.691 0.691
EN 0.309 0.038 8.080 0.000 0.718 0.718
SC ~~
IN 0.169 0.028 6.038 0.000 0.528 0.528
EN 0.275 0.038 7.180 0.000 0.771 0.771
IN ~~
EN 0.257 0.035 7.422 0.000 0.671 0.671
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EL 0.434 0.054 8.040 0.000 1.000 1.000
SC 0.299 0.056 5.337 0.000 1.000 1.000
IN 0.344 0.051 6.741 0.000 1.000 1.000
EN 0.427 0.058 7.335 0.000 1.000 1.000
.Q4_1 0.290 0.025 11.525 0.000 0.290 0.400
.Q4_2 0.268 0.023 11.664 0.000 0.268 0.438
.Q4_3 0.263 0.023 11.375 0.000 0.263 0.366
.Q4_4 0.254 0.022 11.314 0.000 0.254 0.354
.Q4_5 0.332 0.028 11.665 0.000 0.332 0.438
.Q4_8 0.346 0.029 11.778 0.000 0.346 0.475
.Q4_9 0.490 0.041 11.912 0.000 0.490 0.527
.Q4_10 0.264 0.023 11.575 0.000 0.264 0.413
.Q4_11 0.391 0.034 11.645 0.000 0.391 0.432
.Q4_15 0.377 0.032 11.804 0.000 0.377 0.484
.Q4_16 0.479 0.040 11.975 0.000 0.479 0.555
.Q4_17 0.545 0.045 12.115 0.000 0.545 0.632
.Q4_18 0.206 0.018 11.189 0.000 0.206 0.331
.Q4_19 0.403 0.035 11.629 0.000 0.403 0.428
.Q5_1 0.604 0.051 11.879 0.000 0.604 0.669
.Q5_2 0.630 0.054 11.722 0.000 0.630 0.617
.Q5_3 0.614 0.053 11.547 0.000 0.614 0.568
.Q5_4 0.452 0.043 10.396 0.000 0.452 0.373
.Q5_5 0.403 0.039 10.275 0.000 0.403 0.360
.Q5_6 0.333 0.031 10.569 0.000 0.333 0.394
.Q5_8 0.449 0.043 10.555 0.000 0.449 0.392
.Q5_12 0.654 0.055 11.793 0.000 0.654 0.640
.Q6_1 0.387 0.033 11.660 0.000 0.387 0.529
.Q6_2 0.315 0.029 10.974 0.000 0.315 0.382
.Q6_3 0.308 0.028 10.838 0.000 0.308 0.362
.Q6_4 0.347 0.031 11.072 0.000 0.347 0.397
.Q6_5 0.955 0.078 12.246 0.000 0.955 0.792
.Q6_6 0.238 0.022 11.001 0.000 0.238 0.386
.Q6_7 0.249 0.024 10.541 0.000 0.249 0.325
.Q6_8 0.228 0.022 10.571 0.000 0.228 0.328
.Q6_11 0.587 0.049 11.913 0.000 0.587 0.617
.Q7_2 0.359 0.033 10.914 0.000 0.359 0.457
.Q7_4 0.520 0.045 11.561 0.000 0.520 0.587
.Q7_5 0.392 0.036 10.815 0.000 0.392 0.442
.Q7_7 0.576 0.051 11.202 0.000 0.576 0.507
.Q7_8 0.356 0.034 10.549 0.000 0.356 0.406
.Q7_12 0.633 0.055 11.446 0.000 0.633 0.558
.Q7_13 1.046 0.085 12.275 0.000 1.046 0.859
.Q7_14 0.644 0.056 11.586 0.000 0.644 0.593fit1 <- lavaan::cfa(mod1, data=mydata, ordered=T)Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
The variance-covariance matrix of the estimated parameters (vcov)
does not appear to be positive definite! The smallest eigenvalue
(= -1.720588e-17) is smaller than zero. This may be a symptom that
the model is not identified.summary(fit1, standardized=T, fit.measures=T)lavaan 0.6-7 ended normally after 67 iterations
Estimator DWLS
Optimization method NLMINB
Number of free parameters 201
Number of observations 312
Model Test User Model:
Standard Robust
Test Statistic 2549.695 2222.269
Degrees of freedom 696 696
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.437
Shift parameter 447.847
simple second-order correction
Model Test Baseline Model:
Test statistic 113152.945 17274.138
Degrees of freedom 741 741
P-value 0.000 0.000
Scaling correction factor 6.799
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.984 0.908
Tucker-Lewis Index (TLI) 0.982 0.902
Robust Comparative Fit Index (CFI) NA
Robust Tucker-Lewis Index (TLI) NA
Root Mean Square Error of Approximation:
RMSEA 0.093 0.084
90 Percent confidence interval - lower 0.089 0.080
90 Percent confidence interval - upper 0.096 0.088
P-value RMSEA <= 0.05 0.000 0.000
Robust RMSEA NA
90 Percent confidence interval - lower NA
90 Percent confidence interval - upper NA
Standardized Root Mean Square Residual:
SRMR 0.074 0.074
Parameter Estimates:
Standard errors Robust.sem
Information Expected
Information saturated (h1) model Unstructured
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EL =~
Q4_1 1.000 0.815 0.815
Q4_2 0.958 0.030 31.941 0.000 0.781 0.781
Q4_3 1.039 0.029 36.179 0.000 0.846 0.846
Q4_4 1.042 0.028 37.342 0.000 0.849 0.849
Q4_5 0.981 0.033 29.651 0.000 0.799 0.799
Q4_8 0.958 0.034 27.917 0.000 0.781 0.781
Q4_9 0.953 0.035 27.360 0.000 0.776 0.776
Q4_10 1.007 0.031 32.389 0.000 0.821 0.821
Q4_11 1.018 0.033 31.193 0.000 0.829 0.829
Q4_15 0.957 0.030 31.435 0.000 0.780 0.780
Q4_16 0.910 0.031 28.934 0.000 0.742 0.742
Q4_17 0.821 0.038 21.493 0.000 0.669 0.669
Q4_18 1.051 0.029 35.739 0.000 0.856 0.856
Q4_19 1.007 0.030 33.139 0.000 0.821 0.821
SC =~
Q5_1 1.000 0.783 0.783
Q5_2 0.860 0.046 18.535 0.000 0.673 0.673
Q5_3 0.926 0.052 17.815 0.000 0.725 0.725
Q5_4 1.046 0.046 22.706 0.000 0.819 0.819
Q5_5 1.077 0.045 23.921 0.000 0.843 0.843
Q5_6 1.027 0.049 21.132 0.000 0.804 0.804
Q5_8 0.995 0.051 19.418 0.000 0.779 0.779
Q5_12 1.017 0.051 19.765 0.000 0.796 0.796
IN =~
Q6_1 1.000 0.757 0.757
Q6_2 1.108 0.045 24.546 0.000 0.840 0.840
Q6_3 1.058 0.049 21.527 0.000 0.801 0.801
Q6_4 1.062 0.046 22.874 0.000 0.804 0.804
Q6_5 0.731 0.057 12.885 0.000 0.554 0.554
Q6_6 1.124 0.052 21.505 0.000 0.851 0.851
Q6_7 1.193 0.059 20.355 0.000 0.903 0.903
Q6_8 1.121 0.052 21.466 0.000 0.849 0.849
Q6_11 1.130 0.062 18.216 0.000 0.856 0.856
EN =~
Q7_2 1.000 0.831 0.831
Q7_4 0.843 0.038 22.316 0.000 0.701 0.701
Q7_5 0.948 0.038 25.129 0.000 0.788 0.788
Q7_7 0.837 0.043 19.240 0.000 0.695 0.695
Q7_8 0.959 0.040 24.249 0.000 0.797 0.797
Q7_12 0.844 0.044 19.218 0.000 0.702 0.702
Q7_13 0.484 0.054 8.890 0.000 0.403 0.403
Q7_14 0.803 0.046 17.628 0.000 0.668 0.668
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EL ~~
SC 0.385 0.031 12.441 0.000 0.603 0.603
IN 0.440 0.033 13.191 0.000 0.713 0.713
EN 0.491 0.028 17.588 0.000 0.725 0.725
SC ~~
IN 0.356 0.033 10.644 0.000 0.600 0.600
EN 0.490 0.032 15.155 0.000 0.753 0.753
IN ~~
EN 0.453 0.035 13.107 0.000 0.720 0.720
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.Q4_1 0.000 0.000 0.000
.Q4_2 0.000 0.000 0.000
.Q4_3 0.000 0.000 0.000
.Q4_4 0.000 0.000 0.000
.Q4_5 0.000 0.000 0.000
.Q4_8 0.000 0.000 0.000
.Q4_9 0.000 0.000 0.000
.Q4_10 0.000 0.000 0.000
.Q4_11 0.000 0.000 0.000
.Q4_15 0.000 0.000 0.000
.Q4_16 0.000 0.000 0.000
.Q4_17 0.000 0.000 0.000
.Q4_18 0.000 0.000 0.000
.Q4_19 0.000 0.000 0.000
.Q5_1 0.000 0.000 0.000
.Q5_2 0.000 0.000 0.000
.Q5_3 0.000 0.000 0.000
.Q5_4 0.000 0.000 0.000
.Q5_5 0.000 0.000 0.000
.Q5_6 0.000 0.000 0.000
.Q5_8 0.000 0.000 0.000
.Q5_12 0.000 0.000 0.000
.Q6_1 0.000 0.000 0.000
.Q6_2 0.000 0.000 0.000
.Q6_3 0.000 0.000 0.000
.Q6_4 0.000 0.000 0.000
.Q6_5 0.000 0.000 0.000
.Q6_6 0.000 0.000 0.000
.Q6_7 0.000 0.000 0.000
.Q6_8 0.000 0.000 0.000
.Q6_11 0.000 0.000 0.000
.Q7_2 0.000 0.000 0.000
.Q7_4 0.000 0.000 0.000
.Q7_5 0.000 0.000 0.000
.Q7_7 0.000 0.000 0.000
.Q7_8 0.000 0.000 0.000
.Q7_12 0.000 0.000 0.000
.Q7_13 0.000 0.000 0.000
.Q7_14 0.000 0.000 0.000
EL 0.000 0.000 0.000
SC 0.000 0.000 0.000
IN 0.000 0.000 0.000
EN 0.000 0.000 0.000
Thresholds:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
Q4_1|t1 -1.062 0.088 -12.101 0.000 -1.062 -1.062
Q4_1|t2 0.153 0.071 2.147 0.032 0.153 0.153
Q4_1|t3 1.449 0.106 13.658 0.000 1.449 1.449
Q4_1|t4 2.232 0.193 11.570 0.000 2.232 2.232
Q4_2|t1 -0.993 0.085 -11.632 0.000 -0.993 -0.993
Q4_2|t2 0.521 0.075 6.972 0.000 0.521 0.521
Q4_2|t3 1.732 0.127 13.613 0.000 1.732 1.732
Q4_2|t4 2.232 0.193 11.570 0.000 2.232 2.232
Q4_3|t1 -1.198 0.093 -12.870 0.000 -1.198 -1.198
Q4_3|t2 0.040 0.071 0.565 0.572 0.040 0.040
Q4_3|t3 1.449 0.106 13.658 0.000 1.449 1.449
Q4_3|t4 2.006 0.157 12.746 0.000 2.006 2.006
Q4_4|t1 -1.150 0.091 -12.627 0.000 -1.150 -1.150
Q4_4|t2 -0.153 0.071 -2.147 0.032 -0.153 -0.153
Q4_4|t3 1.426 0.105 13.620 0.000 1.426 1.426
Q4_4|t4 2.144 0.178 12.067 0.000 2.144 2.144
Q4_5|t1 -0.930 0.083 -11.142 0.000 -0.930 -0.930
Q4_5|t2 0.448 0.074 6.082 0.000 0.448 0.448
Q4_5|t3 1.383 0.102 13.529 0.000 1.383 1.383
Q4_5|t4 2.232 0.193 11.570 0.000 2.232 2.232
Q4_8|t1 -0.812 0.080 -10.117 0.000 -0.812 -0.812
Q4_8|t2 0.457 0.074 6.194 0.000 0.457 0.457
Q4_8|t3 1.547 0.113 13.751 0.000 1.547 1.547
Q4_8|t4 2.341 0.215 10.896 0.000 2.341 2.341
Q4_9|t1 -0.955 0.084 -11.340 0.000 -0.955 -0.955
Q4_9|t2 0.235 0.072 3.275 0.001 0.235 0.235
Q4_9|t3 1.090 0.089 12.282 0.000 1.090 1.090
Q4_9|t4 2.070 0.166 12.448 0.000 2.070 2.070
Q4_10|t1 -1.198 0.093 -12.870 0.000 -1.198 -1.198
Q4_10|t2 -0.227 0.072 -3.163 0.002 -0.227 -0.227
Q4_10|t3 1.603 0.117 13.751 0.000 1.603 1.603
Q4_10|t4 2.232 0.193 11.570 0.000 2.232 2.232
Q4_11|t1 -1.007 0.086 -11.727 0.000 -1.007 -1.007
Q4_11|t2 0.032 0.071 0.452 0.651 0.032 0.032
Q4_11|t3 1.150 0.091 12.627 0.000 1.150 1.150
Q4_11|t4 2.006 0.157 12.746 0.000 2.006 2.006
Q4_15|t1 -0.905 0.083 -10.941 0.000 -0.905 -0.905
Q4_15|t2 0.302 0.072 4.176 0.000 0.302 0.302
Q4_15|t3 1.342 0.100 13.421 0.000 1.342 1.342
Q4_15|t4 2.489 0.251 9.915 0.000 2.489 2.489
Q4_16|t1 -0.823 0.081 -10.222 0.000 -0.823 -0.823
Q4_16|t2 0.170 0.071 2.373 0.018 0.170 0.170
Q4_16|t3 1.304 0.098 13.300 0.000 1.304 1.304
Q4_16|t4 2.341 0.215 10.896 0.000 2.341 2.341
Q4_17|t1 -0.539 0.075 -7.194 0.000 -0.539 -0.539
Q4_17|t2 0.521 0.075 6.972 0.000 0.521 0.521
Q4_17|t3 1.362 0.101 13.477 0.000 1.362 1.362
Q4_17|t4 2.726 0.330 8.259 0.000 2.726 2.726
Q4_18|t1 -1.105 0.089 -12.370 0.000 -1.105 -1.105
Q4_18|t2 0.413 0.073 5.635 0.000 0.413 0.413
Q4_18|t3 1.521 0.111 13.738 0.000 1.521 1.521
Q4_18|t4 2.489 0.251 9.915 0.000 2.489 2.489
Q4_19|t1 -0.967 0.085 -11.438 0.000 -0.967 -0.967
Q4_19|t2 0.000 0.071 0.000 1.000 0.000 0.000
Q4_19|t3 1.105 0.089 12.370 0.000 1.105 1.105
Q4_19|t4 2.006 0.157 12.746 0.000 2.006 2.006
Q5_1|t1 -1.076 0.088 -12.192 0.000 -1.076 -1.076
Q5_1|t2 0.008 0.071 0.113 0.910 0.008 0.008
Q5_1|t3 1.020 0.086 11.822 0.000 1.020 1.020
Q5_1|t4 2.144 0.178 12.067 0.000 2.144 2.144
Q5_2|t1 -1.323 0.099 -13.362 0.000 -1.323 -1.323
Q5_2|t2 -0.521 0.075 -6.972 0.000 -0.521 -0.521
Q5_2|t3 0.502 0.074 6.750 0.000 0.502 0.502
Q5_2|t4 1.697 0.124 13.669 0.000 1.697 1.697
Q5_3|t1 -1.020 0.086 -11.822 0.000 -1.020 -1.020
Q5_3|t2 -0.048 0.071 -0.678 0.498 -0.048 -0.048
Q5_3|t3 0.881 0.082 10.738 0.000 0.881 0.881
Q5_3|t4 1.769 0.131 13.539 0.000 1.769 1.769
Q5_4|t1 -1.404 0.103 -13.577 0.000 -1.404 -1.404
Q5_4|t2 -0.835 0.081 -10.326 0.000 -0.835 -0.835
Q5_4|t3 -0.310 0.072 -4.289 0.000 -0.310 -0.310
Q5_4|t4 1.182 0.092 12.791 0.000 1.182 1.182
Q5_5|t1 -1.521 0.111 -13.738 0.000 -1.521 -1.521
Q5_5|t2 -0.823 0.081 -10.222 0.000 -0.823 -0.823
Q5_5|t3 -0.302 0.072 -4.176 0.000 -0.302 -0.302
Q5_5|t4 1.267 0.096 13.166 0.000 1.267 1.267
Q5_6|t1 -1.449 0.106 -13.658 0.000 -1.449 -1.449
Q5_6|t2 -0.457 0.074 -6.194 0.000 -0.457 -0.457
Q5_6|t3 0.812 0.080 10.117 0.000 0.812 0.812
Q5_6|t4 1.769 0.131 13.539 0.000 1.769 1.769
Q5_8|t1 -1.120 0.090 -12.457 0.000 -1.120 -1.120
Q5_8|t2 -0.378 0.073 -5.187 0.000 -0.378 -0.378
Q5_8|t3 0.586 0.076 7.746 0.000 0.586 0.586
Q5_8|t4 1.664 0.121 13.709 0.000 1.664 1.664
Q5_12|t1 -1.120 0.090 -12.457 0.000 -1.120 -1.120
Q5_12|t2 -0.466 0.074 -6.305 0.000 -0.466 -0.466
Q5_12|t3 0.801 0.080 10.012 0.000 0.801 0.801
Q5_12|t4 1.697 0.124 13.669 0.000 1.697 1.697
Q6_1|t1 0.000 0.071 0.000 1.000 0.000 0.000
Q6_1|t2 1.198 0.093 12.870 0.000 1.198 1.198
Q6_1|t3 1.633 0.119 13.736 0.000 1.633 1.633
Q6_1|t4 2.232 0.193 11.570 0.000 2.232 2.232
Q6_2|t1 -0.605 0.076 -7.965 0.000 -0.605 -0.605
Q6_2|t2 0.790 0.080 9.907 0.000 0.790 0.790
Q6_2|t3 1.362 0.101 13.477 0.000 1.362 1.362
Q6_2|t4 2.144 0.178 12.067 0.000 2.144 2.144
Q6_3|t1 -0.484 0.074 -6.528 0.000 -0.484 -0.484
Q6_3|t2 0.801 0.080 10.012 0.000 0.801 0.801
Q6_3|t3 1.426 0.105 13.620 0.000 1.426 1.426
Q6_3|t4 2.070 0.166 12.448 0.000 2.070 2.070
Q6_4|t1 -0.625 0.076 -8.185 0.000 -0.625 -0.625
Q6_4|t2 0.596 0.076 7.856 0.000 0.596 0.596
Q6_4|t3 1.426 0.105 13.620 0.000 1.426 1.426
Q6_4|t4 2.006 0.157 12.746 0.000 2.006 2.006
Q6_5|t1 -0.779 0.079 -9.801 0.000 -0.779 -0.779
Q6_5|t2 0.293 0.072 4.064 0.000 0.293 0.293
Q6_5|t3 0.905 0.083 10.941 0.000 0.905 0.905
Q6_5|t4 1.732 0.127 13.613 0.000 1.732 1.732
Q6_6|t1 -0.353 0.073 -4.851 0.000 -0.353 -0.353
Q6_6|t2 1.120 0.090 12.457 0.000 1.120 1.120
Q6_6|t3 1.732 0.127 13.613 0.000 1.732 1.732
Q6_6|t4 2.489 0.251 9.915 0.000 2.489 2.489
Q6_7|t1 -0.674 0.077 -8.729 0.000 -0.674 -0.674
Q6_7|t2 0.558 0.075 7.415 0.000 0.558 0.558
Q6_7|t3 1.521 0.111 13.738 0.000 1.521 1.521
Q6_7|t4 2.341 0.215 10.896 0.000 2.341 2.341
Q6_8|t1 -0.846 0.081 -10.430 0.000 -0.846 -0.846
Q6_8|t2 0.577 0.076 7.636 0.000 0.577 0.577
Q6_8|t3 1.574 0.114 13.756 0.000 1.574 1.574
Q6_8|t4 2.232 0.193 11.570 0.000 2.232 2.232
Q6_11|t1 -1.047 0.087 -12.009 0.000 -1.047 -1.047
Q6_11|t2 -0.370 0.073 -5.075 0.000 -0.370 -0.370
Q6_11|t3 0.980 0.085 11.535 0.000 0.980 0.980
Q6_11|t4 1.898 0.144 13.171 0.000 1.898 1.898
Q7_2|t1 -1.076 0.088 -12.192 0.000 -1.076 -1.076
Q7_2|t2 -0.422 0.073 -5.747 0.000 -0.422 -0.422
Q7_2|t3 1.215 0.094 12.947 0.000 1.215 1.215
Q7_2|t4 2.232 0.193 11.570 0.000 2.232 2.232
Q7_4|t1 -1.267 0.096 -13.166 0.000 -1.267 -1.267
Q7_4|t2 -0.422 0.073 -5.747 0.000 -0.422 -0.422
Q7_4|t3 0.869 0.082 10.636 0.000 0.869 0.869
Q7_4|t4 1.851 0.139 13.323 0.000 1.851 1.851
Q7_5|t1 -1.182 0.092 -12.791 0.000 -1.182 -1.182
Q7_5|t2 -0.530 0.075 -7.083 0.000 -0.530 -0.530
Q7_5|t3 0.980 0.085 11.535 0.000 0.980 0.980
Q7_5|t4 1.769 0.131 13.539 0.000 1.769 1.769
Q7_7|t1 -1.547 0.113 -13.751 0.000 -1.547 -1.547
Q7_7|t2 -0.917 0.083 -11.041 0.000 -0.917 -0.917
Q7_7|t3 -0.422 0.073 -5.747 0.000 -0.422 -0.422
Q7_7|t4 1.062 0.088 12.101 0.000 1.062 1.062
Q7_8|t1 -1.285 0.097 -13.235 0.000 -1.285 -1.285
Q7_8|t2 -0.493 0.074 -6.639 0.000 -0.493 -0.493
Q7_8|t3 0.893 0.082 10.840 0.000 0.893 0.893
Q7_8|t4 1.769 0.131 13.539 0.000 1.769 1.769
Q7_12|t1 -1.449 0.106 -13.658 0.000 -1.449 -1.449
Q7_12|t2 -0.930 0.083 -11.142 0.000 -0.930 -0.930
Q7_12|t3 -0.016 0.071 -0.226 0.821 -0.016 -0.016
Q7_12|t4 1.150 0.091 12.627 0.000 1.150 1.150
Q7_13|t1 -1.574 0.114 -13.756 0.000 -1.574 -1.574
Q7_13|t2 -0.893 0.082 -10.840 0.000 -0.893 -0.893
Q7_13|t3 -0.137 0.071 -1.921 0.055 -0.137 -0.137
Q7_13|t4 0.905 0.083 10.941 0.000 0.905 0.905
Q7_14|t1 -1.633 0.119 -13.736 0.000 -1.633 -1.633
Q7_14|t2 -1.007 0.086 -11.727 0.000 -1.007 -1.007
Q7_14|t3 -0.277 0.072 -3.839 0.000 -0.277 -0.277
Q7_14|t4 0.993 0.085 11.632 0.000 0.993 0.993
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EL 0.664 0.034 19.547 0.000 1.000 1.000
SC 0.613 0.047 13.018 0.000 1.000 1.000
IN 0.574 0.051 11.165 0.000 1.000 1.000
EN 0.691 0.043 16.158 0.000 1.000 1.000
.Q4_1 0.336 0.336 0.336
.Q4_2 0.391 0.391 0.391
.Q4_3 0.284 0.284 0.284
.Q4_4 0.280 0.280 0.280
.Q4_5 0.362 0.362 0.362
.Q4_8 0.390 0.390 0.390
.Q4_9 0.398 0.398 0.398
.Q4_10 0.327 0.327 0.327
.Q4_11 0.313 0.313 0.313
.Q4_15 0.392 0.392 0.392
.Q4_16 0.450 0.450 0.450
.Q4_17 0.553 0.553 0.553
.Q4_18 0.267 0.267 0.267
.Q4_19 0.326 0.326 0.326
.Q5_1 0.387 0.387 0.387
.Q5_2 0.547 0.547 0.547
.Q5_3 0.475 0.475 0.475
.Q5_4 0.330 0.330 0.330
.Q5_5 0.289 0.289 0.289
.Q5_6 0.354 0.354 0.354
.Q5_8 0.393 0.393 0.393
.Q5_12 0.366 0.366 0.366
.Q6_1 0.426 0.426 0.426
.Q6_2 0.295 0.295 0.295
.Q6_3 0.358 0.358 0.358
.Q6_4 0.353 0.353 0.353
.Q6_5 0.693 0.693 0.693
.Q6_6 0.275 0.275 0.275
.Q6_7 0.184 0.184 0.184
.Q6_8 0.279 0.279 0.279
.Q6_11 0.267 0.267 0.267
.Q7_2 0.309 0.309 0.309
.Q7_4 0.509 0.509 0.509
.Q7_5 0.380 0.380 0.380
.Q7_7 0.516 0.516 0.516
.Q7_8 0.365 0.365 0.365
.Q7_12 0.508 0.508 0.508
.Q7_13 0.838 0.838 0.838
.Q7_14 0.554 0.554 0.554
Scales y*:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
Q4_1 1.000 1.000 1.000
Q4_2 1.000 1.000 1.000
Q4_3 1.000 1.000 1.000
Q4_4 1.000 1.000 1.000
Q4_5 1.000 1.000 1.000
Q4_8 1.000 1.000 1.000
Q4_9 1.000 1.000 1.000
Q4_10 1.000 1.000 1.000
Q4_11 1.000 1.000 1.000
Q4_15 1.000 1.000 1.000
Q4_16 1.000 1.000 1.000
Q4_17 1.000 1.000 1.000
Q4_18 1.000 1.000 1.000
Q4_19 1.000 1.000 1.000
Q5_1 1.000 1.000 1.000
Q5_2 1.000 1.000 1.000
Q5_3 1.000 1.000 1.000
Q5_4 1.000 1.000 1.000
Q5_5 1.000 1.000 1.000
Q5_6 1.000 1.000 1.000
Q5_8 1.000 1.000 1.000
Q5_12 1.000 1.000 1.000
Q6_1 1.000 1.000 1.000
Q6_2 1.000 1.000 1.000
Q6_3 1.000 1.000 1.000
Q6_4 1.000 1.000 1.000
Q6_5 1.000 1.000 1.000
Q6_6 1.000 1.000 1.000
Q6_7 1.000 1.000 1.000
Q6_8 1.000 1.000 1.000
Q6_11 1.000 1.000 1.000
Q7_2 1.000 1.000 1.000
Q7_4 1.000 1.000 1.000
Q7_5 1.000 1.000 1.000
Q7_7 1.000 1.000 1.000
Q7_8 1.000 1.000 1.000
Q7_12 1.000 1.000 1.000
Q7_13 1.000 1.000 1.000
Q7_14 1.000 1.000 1.000# get the model implied instrumental variables
miivs(mod1)Warning in if (trySolve(BetaNA)) {: the condition has length > 1 and only the
first element will be usedModel Equation Information
LHS RHS
Q4_2 Q4_1
Q4_3 Q4_1
Q4_4 Q4_1
Q4_5 Q4_1
Q4_8 Q4_1
Q4_9 Q4_1
Q4_10 Q4_1
Q4_11 Q4_1
Q4_15 Q4_1
Q4_16 Q4_1
Q4_17 Q4_1
Q4_18 Q4_1
Q4_19 Q4_1
Q5_2 Q5_1
Q5_3 Q5_1
Q5_4 Q5_1
Q5_5 Q5_1
Q5_6 Q5_1
Q5_8 Q5_1
Q5_12 Q5_1
Q6_2 Q6_1
Q6_3 Q6_1
Q6_4 Q6_1
Q6_5 Q6_1
Q6_6 Q6_1
Q6_7 Q6_1
Q6_8 Q6_1
Q6_11 Q6_1
Q7_4 Q7_2
Q7_5 Q7_2
Q7_7 Q7_2
Q7_8 Q7_2
Q7_12 Q7_2
Q7_13 Q7_2
Q7_14 Q7_2
MIIVs
Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_5, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_2, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_2, Q5_3, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_2, Q5_3, Q5_4, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_2, Q5_3, Q5_4, Q5_5, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_2, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_2, Q6_3, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_2, Q6_3, Q6_4, Q6_6, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_2, Q6_3, Q6_4, Q6_5, Q6_7, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_8, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_11, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q7_2, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_4, Q7_7, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_4, Q7_5, Q7_8, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_4, Q7_5, Q7_7, Q7_12, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_4, Q7_5, Q7_7, Q7_8, Q7_13, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_14
Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_8, Q4_9, Q4_10, Q4_11, Q4_15, Q4_16, Q4_17, Q4_18, Q4_19, Q5_1, Q5_2, Q5_3, Q5_4, Q5_5, Q5_6, Q5_8, Q5_12, Q6_1, Q6_2, Q6_3, Q6_4, Q6_5, Q6_6, Q6_7, Q6_8, Q6_11, Q7_4, Q7_5, Q7_7, Q7_8, Q7_12, Q7_13 fit1 <- MIIVsem::miive(mod1, data=mydata)Warning in if (trySolve(BetaNA)) {: the condition has length > 1 and only the
first element will be usedsummary(fit1)MIIVsem (0.5.5) results
Number of observations 312
Number of equations 35
Estimator MIIV-2SLS
Standard Errors standard
Missing listwise
Parameter Estimates:
STRUCTURAL COEFFICIENTS:
Estimate Std.Err z-value P(>|z|) Sargan df P(Chi)
EL =~
Q4_1 1.000
Q4_2 0.813 0.050 16.136 0.000 57.558 36 0.013
Q4_3 0.978 0.052 18.928 0.000 45.111 36 0.142
Q4_4 0.950 0.054 17.449 0.000 52.226 36 0.039
Q4_5 0.812 0.064 12.705 0.000 89.531 36 0.000
Q4_8 0.754 0.064 11.764 0.000 89.092 36 0.000
Q4_9 0.770 0.072 10.678 0.000 126.594 36 0.000
Q4_10 0.795 0.053 15.081 0.000 69.268 36 0.001
Q4_11 0.906 0.065 13.909 0.000 97.157 36 0.000
Q4_15 0.781 0.063 12.397 0.000 96.437 36 0.000
Q4_16 0.836 0.067 12.512 0.000 78.464 36 0.000
Q4_17 0.674 0.069 9.729 0.000 93.603 36 0.000
Q4_18 0.845 0.053 16.028 0.000 69.339 36 0.001
Q4_19 0.891 0.068 13.201 0.000 118.605 36 0.000
EN =~
Q7_2 1.000
Q7_4 0.808 0.067 12.136 0.000 65.024 36 0.002
Q7_5 0.933 0.066 14.066 0.000 55.791 36 0.019
Q7_7 0.853 0.078 10.922 0.000 99.736 36 0.000
Q7_8 0.883 0.065 13.532 0.000 86.489 36 0.000
Q7_12 0.838 0.082 10.239 0.000 112.196 36 0.000
Q7_13 0.411 0.088 4.692 0.000 108.095 36 0.000
Q7_14 0.761 0.080 9.459 0.000 102.168 36 0.000
IN =~
Q6_1 1.000
Q6_2 1.004 0.063 16.000 0.000 81.381 36 0.000
Q6_3 0.949 0.065 14.557 0.000 79.387 36 0.000
Q6_4 0.975 0.069 14.101 0.000 82.202 36 0.000
Q6_5 0.615 0.089 6.914 0.000 64.094 36 0.003
Q6_6 0.682 0.059 11.518 0.000 123.462 36 0.000
Q6_7 0.851 0.066 12.807 0.000 118.819 36 0.000
Q6_8 0.817 0.063 12.891 0.000 100.842 36 0.000
Q6_11 0.608 0.080 7.559 0.000 132.969 36 0.000
SC =~
Q5_1 1.000
Q5_2 0.836 0.078 10.755 0.000 74.900 36 0.000
Q5_3 0.951 0.083 11.438 0.000 50.812 36 0.052
Q5_4 0.803 0.089 9.041 0.000 155.872 36 0.000
Q5_5 0.829 0.088 9.452 0.000 136.462 36 0.000
Q5_6 0.772 0.076 10.183 0.000 93.538 36 0.000
Q5_8 0.808 0.086 9.428 0.000 124.326 36 0.000
Q5_12 0.794 0.084 9.500 0.000 81.247 36 0.000
INTERCEPTS:
Estimate Std.Err z-value P(>|z|)
Q4_1 0.000
Q4_10 0.033 0.049 0.684 0.494
Q4_11 0.038 0.061 0.627 0.531
Q4_15 -0.222 0.059 -3.777 0.000
Q4_16 -0.149 0.062 -2.392 0.017
Q4_17 -0.487 0.065 -7.535 0.000
Q4_18 -0.202 0.049 -4.098 0.000
Q4_19 0.042 0.063 0.665 0.506
Q4_2 -0.302 0.047 -6.463 0.000
Q4_3 0.070 0.048 1.456 0.145
Q4_4 0.117 0.051 2.301 0.021
Q4_5 -0.251 0.060 -4.208 0.000
Q4_8 -0.348 0.060 -5.827 0.000
Q4_9 -0.130 0.067 -1.927 0.054
Q5_1 0.000
Q5_12 0.181 0.070 2.601 0.009
Q5_2 0.355 0.063 5.628 0.000
Q5_3 0.044 0.069 0.634 0.526
Q5_4 0.839 0.074 11.358 0.000
Q5_5 0.845 0.073 11.571 0.000
Q5_6 0.216 0.063 3.414 0.001
Q5_8 0.226 0.071 3.175 0.001
Q6_1 0.000
Q6_11 0.492 0.119 4.125 0.000
Q6_2 0.371 0.092 4.017 0.000
Q6_3 0.246 0.096 2.556 0.011
Q6_4 0.396 0.103 3.864 0.000
Q6_5 0.203 0.132 1.540 0.124
Q6_6 -0.282 0.088 -3.212 0.001
Q6_7 0.236 0.099 2.390 0.017
Q6_8 0.233 0.094 2.477 0.013
Q7_12 0.677 0.064 10.526 0.000
Q7_13 0.639 0.069 9.266 0.000
Q7_14 0.829 0.063 13.114 0.000
Q7_2 0.000
Q7_4 0.070 0.052 1.346 0.178
Q7_5 0.114 0.052 2.193 0.028
Q7_7 0.868 0.061 14.165 0.000
Q7_8 0.125 0.051 2.457 0.014 fit1 <- MIIVsem::miive(
mod1, data=mydata,
ordered=c(
paste0("Q4_",c(1:5,8:11, 15:19)),
paste0("Q5_",c(1:6, 8, 12)),
paste0("Q6_",c(1:8, 11)),
paste0("Q7_",c(2, 4:5, 7:8, 12:14))
)
)Warning in if (trySolve(BetaNA)) {: the condition has length > 1 and only the
first element will be usedWarning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
The variance-covariance matrix of the estimated parameters (vcov)
does not appear to be positive definite! The smallest eigenvalue
(= -2.521472e-16) is smaller than zero. This may be a symptom that
the model is not identified.summary(fit1)MIIVsem (0.5.5) results
Number of observations 312
Number of equations 35
Estimator MIIV-2SLS (PIV)
Standard Errors standard
Missing listwise
Parameter Estimates:
STRUCTURAL COEFFICIENTS:
Estimate Std.Err z-value P(>|z|) Sargan df P(Chi)
EL =~
Q4_1 1.000
Q4_2 0.872 0.034 26.013 0.000
Q4_3 0.957 0.031 30.734 0.000
Q4_4 0.919 0.039 23.338 0.000
Q4_5 0.767 0.045 16.961 0.000
Q4_8 0.728 0.046 15.666 0.000
Q4_9 0.653 0.051 12.794 0.000
Q4_10 0.824 0.036 22.656 0.000
Q4_11 0.787 0.042 18.937 0.000
Q4_15 0.731 0.041 17.718 0.000
Q4_16 0.776 0.043 18.051 0.000
Q4_17 0.626 0.051 12.294 0.000
Q4_18 0.896 0.041 21.975 0.000
Q4_19 0.748 0.042 17.885 0.000
EN =~
Q7_2 1.000
Q7_4 0.674 0.050 13.359 0.000
Q7_5 0.809 0.047 17.046 0.000
Q7_7 0.642 0.056 11.396 0.000
Q7_8 0.746 0.048 15.671 0.000
Q7_12 0.644 0.060 10.708 0.000
Q7_13 0.298 0.067 4.469 0.000
Q7_14 0.571 0.060 9.481 0.000
IN =~
Q6_1 1.000
Q6_2 0.834 0.047 17.890 0.000
Q6_3 0.762 0.048 15.791 0.000
Q6_4 0.777 0.045 17.420 0.000
Q6_5 0.442 0.053 8.271 0.000
Q6_6 0.661 0.051 12.916 0.000
Q6_7 0.737 0.051 14.534 0.000
Q6_8 0.741 0.049 14.991 0.000
Q6_11 0.473 0.060 7.843 0.000
SC =~
Q5_1 1.000
Q5_2 0.782 0.067 11.646 0.000
Q5_3 0.846 0.060 13.996 0.000
Q5_4 0.667 0.069 9.651 0.000
Q5_5 0.728 0.074 9.899 0.000
Q5_6 0.739 0.062 11.990 0.000
Q5_8 0.684 0.065 10.478 0.000
Q5_12 0.679 0.069 9.802 0.000
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 dbplyr_1.4.4
[29] htmlwidgets_1.5.1 rlang_0.4.7 rstudioapi_0.11 visNetwork_2.0.9
[33] generics_0.0.2 zoo_1.8-8 jsonlite_1.7.0 magrittr_1.5
[37] Matrix_1.2-18 Rcpp_1.0.5 munsell_0.5.0 fansi_0.4.1
[41] visdat_0.5.3 lifecycle_0.2.0 stringi_1.4.6 multcomp_1.4-13
[45] yaml_2.2.1 grid_4.0.2 blob_1.2.1 parallel_4.0.2
[49] promises_1.1.1 crayon_1.3.4 haven_2.3.1 splines_4.0.2
[53] hms_0.5.3 tmvnsim_1.0-2 knitr_1.29 pillar_1.4.6
[57] estimability_1.3 codetools_0.2-16 stats4_4.0.2 reprex_0.3.0
[61] glue_1.4.1 evaluate_0.14 modelr_0.1.8 vctrs_0.3.2
[65] httpuv_1.5.4 cellranger_1.1.0 gtable_0.3.0 assertthat_0.2.1
[69] xfun_0.19 broom_0.7.0 coda_0.19-3 later_1.1.0.1
[73] viridisLite_0.3.0 survival_3.2-3 DiagrammeR_1.0.6.1 TH.data_1.0-10
[77] ellipsis_0.3.1