The code to run the meta-analysis requires `R`, `Stan`, and the ability to compile `RMarkdown` documents (e.g., via `RStudio`). In addition, plenty of RAM (probably at least 16 GB, the machine we used had 32 GB) will be necessary to fit the models and produce all results reports.
Each subcomponents contains a wiki describing the files in detail.
The full `sessionInfo()` of the lates run is:
R version 3.4.0 (2017-04-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1
Matrix products: default
locale:
[1] LC_COLLATE=German_Switzerland.1252 LC_CTYPE=German_Switzerland.1252
[3] LC_MONETARY=German_Switzerland.1252 LC_NUMERIC=C
[5] LC_TIME=German_Switzerland.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] latticeExtra_0.6-28 RColorBrewer_1.1-2 lattice_0.20-35
[4] tidyr_0.6.3 rstan_2.16.2 StanHeaders_2.16.0-1
[7] ggplot2_2.2.1 reshape2_1.4.2 dplyr_0.5.0
[10] devtools_1.13.1
loaded via a namespace (and not attached):
[1] Rcpp_0.12.11 magrittr_1.5 munsell_0.4.3 colorspace_1.3-2
[5] R6_2.2.1 rlang_0.1.1 stringr_1.2.0 plyr_1.8.4
[9] tools_3.4.0 grid_3.4.0 gtable_0.2.0 DBI_0.6-1
[13] withr_1.0.2 fortunes_1.5-4 lazyeval_0.2.0 assertthat_0.2.0
[17] digest_0.6.12 tibble_1.3.1 gridExtra_2.2.1 memoise_1.1.0
[21] inline_0.3.14 stringi_1.1.5 compiler_3.4.0 scales_0.4.1
[25] stats4_3.4.0
