Installation

You can install the released version of evalITR from CRAN with:

# Install release version from CRAN (updating evalITR is the same command)
install.packages("evalITR")

Or, you can install the development version of evalITR from GitHub with:

# install.packages("devtools")
devtools::install_github("MichaelLLi/evalITR", ref = "causal-ml")

If you want to use the latest version of the package, you can install the development version of evalITR by specifying the branch name in devtools::install_github.

Parallelization

(Optional) if you have multiple cores, we recommendate using multisession futures and processing in parallel. This would increase computation efficiency and reduce the time to fit the model.

library(furrr)
library(future.apply)

# check the number of cores
parallel::detectCores()

# set the number of cores
nworkers <- 4
plan(multisession, workers =nworkers)