Setup for Causal Inference and Causal Data Science Course – Causal Inference and Causal Data Science Summerschool

We will work with R. You can use your preferred way of working in R to do the practicals. Our preferred way is this:

Create a new folder with a good name, e.g., practicals_causal_datascience
Open RStudio
Create a new project from RStudio, which you associate with the folder
Create a raw_data subfolder
Create an R script for the current practical, e.g., introduction.R
Create your well-documented and well-styled code in this R script

We try to make our practicals light in the number of required packages, but the packages below are needed. You can install them via:

needed_packages <- c(
  "data.table", "broom", "purrr", "dagitty", "ggplot2", "dplyr", "marginaleffects",
  "MatchIt","survey","tableone"
)
cran_repo <- "https://mirror.lyrahosting.com/CRAN/" # <- a CRAN mirror in the Netherlands, can select another one from here https://cran.r-project.org/mirrors.html

available_pkgs <- available.packages(repos = cran_repo)

for (pkg in needed_packages) {
  if (!pkg %in% rownames(available_pkgs)) {
    warning(sprintf("Package %s is not available from the configured CRAN repo.", sQuote(pkg)))
    next
  }

  installed_version <- tryCatch(
    as.character(packageVersion(pkg)),
    error = function(e) NA_character_
  )
  cran_version <- available_pkgs[pkg, "Version"]

  if (is.na(installed_version) || compareVersion(installed_version, cran_version) < 0) {
    install.packages(pkg, repos = cran_repo)
  }
}