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]

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RCT.pdf |RCT.html✨
RCT/json (API)
NEWS

Peer review:

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

On CRAN:

9 exports 6 stars 2.40 score 44 dependencies 7 mentions 22 scripts 532 downloads

Last updated 7 months agofrom:be7ddc3788. Checks:OK: 7. Indexed: yes.

Exports:balance_regressionbalance_tableimpact_evalN_minntile_labelsummary_statisticstau_mintau_min_probabilitytreatment_assign

Dependencies:backportsbroomclicolorspacecpp11dplyrestimatrfansifarverforcatsFormulagenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpracmapurrrR6RColorBrewerRcppRcppEigenrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr