RCT: 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) <arXiv:1607.00698>.

Version: 1.0.2
Imports: dplyr, purrr, glue, rlang, tidyr, stringr, MASS, pracma, lfe, broom, forcats, magrittr, ggplot2, utils, tidyselect (≥ 1.0.0)
Suggests: knitr, rmarkdown, testthat, qpdf
Published: 2020-05-13
Author: Isidoro Garcia-Urquieta [aut, cre]
Maintainer: Isidoro Garcia-Urquieta <isidoro.gu at gmail.com>
License: GPL-2
NeedsCompilation: no
Citation: RCT citation info
Materials: README NEWS
CRAN checks: RCT results

Downloads:

Reference manual: RCT.pdf
Vignettes: my-vignette
Package source: RCT_1.0.2.tar.gz
Windows binaries: r-devel: RCT_1.0.2.zip, r-release: RCT_1.0.2.zip, r-oldrel: RCT_1.0.2.zip
macOS binaries: r-release: RCT_1.0.2.tgz, r-oldrel: RCT_1.0.2.tgz
Old sources: RCT archive

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