Assign Treatments, Power Calculations, Balances, Impact Evaluation of Experiments

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 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) .


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install.packages("RCT")

1.0.3 by Isidoro Garcia-Urquieta, 3 months ago


Browse source code at https://github.com/cran/RCT


Authors: Isidoro Garcia-Urquieta [aut, cre]


Documentation:   PDF Manual  


GPL-2 license


Imports dplyr, purrr, glue, rlang, tidyr, stringr, MASS, pracma, lfe, broom, forcats, magrittr, ggplot2, utils, tidyselect

Suggests knitr, rmarkdown, testthat, qpdf


See at CRAN