RCT: Assign Treatments, Power Calculations, Balances, ImpactEvaluation 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) <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 |
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