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 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) .


Reference manual

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1.1 by Isidoro Garcia-Urquieta, a month ago

Browse source code at

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