Last updated: 2020-04-06

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Knit directory: research/

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Introduction/ Motivation

Suppose we have results from several experiments on the effect of the same drug. That is, for each of \(J\) experiments, we have an estimated effect and standard error, \((y_j, \sigma_j)\). How should we combine these data into an overall effect estimate and what is the error of the overall effect?

summary(cars)
     speed           dist       
 Min.   : 4.0   Min.   :  2.00  
 1st Qu.:12.0   1st Qu.: 26.00  
 Median :15.0   Median : 36.00  
 Mean   :15.4   Mean   : 42.98  
 3rd Qu.:19.0   3rd Qu.: 56.00  
 Max.   :25.0   Max.   :120.00  

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Version Author Date
befc64c DBomber60 2020-04-06

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sessionInfo()
R version 3.6.2 (2019-12-12)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Catalina 10.15

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] workflowr_1.6.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.3      rprojroot_1.3-2 digest_0.6.23   later_1.0.0    
 [5] R6_2.4.1        backports_1.1.5 git2r_0.26.1    magrittr_1.5   
 [9] evaluate_0.14   stringi_1.4.5   rlang_0.4.4     fs_1.3.1       
[13] promises_1.1.0  whisker_0.4     rmarkdown_2.1   tools_3.6.2    
[17] stringr_1.4.0   glue_1.3.1      httpuv_1.5.2    xfun_0.12      
[21] yaml_2.2.0      compiler_3.6.2  htmltools_0.4.0 knitr_1.27