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) <doi:10.48550/arXiv.1607.00698>.
Version: 1.2 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 Published: 2024-02-21 DOI: 10.32614/CRAN.package.RCT 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=RCT to link to this page.
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