Assign Treatments, Power Calculations, Balances, Impact Evaluation of Experiments R package RCT version 1.2 Assists in the whole process of designing and evaluating Randomized Control Trials. Robust treatment assignment by strata/blocks, that handles misfits; Power calculations of the minimum detectable treatment effect or minimum populations; Balance tables of T-test of covariates; Balance Regression: (treatment ~ all x variables) with F-test of null model; Impact_evaluation: Impact evaluation regressions. This function gives you the option to include control_vars, fixed effect variables, cluster variables (for robust SE), multiple endogenous variables and multiple heterogeneous variables (to test treatment effect heterogeneity) summary_statistics: Function that creates a summary statistics table with statistics rank observations in n groups: Creates a factor variable with n groups. Each group has a min and max label attach to each category. Athey, Susan, and Guido W. Imbens (2017) <arXiv:1607.00698>. Software Imports: dplyr, purrr, glue, rlang, tidyr, stringr, MASS, pracma, estimatr, broom (>= 1.0.0), forcats, magrittr, ggplot2, utils, tidyselect (>= 1.0.0) Suggests: knitr, rmarkdown, testthat Isidoro Garcia-Urquieta <isidoro.gu@gmail.com> Comprehensive R Archive Network (CRAN) Isidoro Garcia-Urquieta [aut, cre] GPL-2 2024-02-21 application/tgz https://CRAN.R-project.org/package=RCT doi:10.32614/CRAN.package.RCT