Package: RCT 1.2

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 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) <arxiv:1607.00698>.

Authors:Isidoro Garcia-Urquieta [aut, cre]

RCT_1.2.tar.gz
RCT_1.2.zip(r-4.5)RCT_1.2.zip(r-4.4)RCT_1.2.zip(r-4.3)
RCT_1.2.tgz(r-4.5-any)RCT_1.2.tgz(r-4.4-any)RCT_1.2.tgz(r-4.3-any)
RCT_1.2.tar.gz(r-4.5-noble)RCT_1.2.tar.gz(r-4.4-noble)
RCT_1.2.tgz(r-4.4-emscripten)RCT_1.2.tgz(r-4.3-emscripten)
RCT.pdf |RCT.html
RCT/json (API)
NEWS

# Install 'RCT' in R:
install.packages('RCT', repos = c('https://isidorogu.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/isidorogu/rct/issues

On CRAN:

Conda:

5.68 score 6 stars 23 scripts 393 downloads 7 mentions 9 exports 44 dependencies

Last updated 1 years agofrom:be7ddc3788. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 17 2025
R-4.5-winOKMar 17 2025
R-4.5-macOKMar 17 2025
R-4.5-linuxOKMar 17 2025
R-4.4-winOKMar 17 2025
R-4.4-macOKMar 17 2025
R-4.4-linuxOKMar 17 2025
R-4.3-winOKMar 17 2025
R-4.3-macOKMar 17 2025

Exports:balance_regressionbalance_tableimpact_evalN_minntile_labelsummary_statisticstau_mintau_min_probabilitytreatment_assign

Dependencies:backportsbroomclicolorspacecpp11dplyrestimatrfansifarverforcatsFormulagenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpracmapurrrR6RColorBrewerRcppRcppEigenrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Randomized Control Trials Design, Assignment and Evaluation

Rendered frommy-vignette.Rmdusingknitr::rmarkdownon Mar 17 2025.

Last update: 2021-01-31
Started: 2020-03-23