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RCTrep

Validation of Estimates of Treatment Effects in Observational Data

v1.2.0 · Nov 2, 2023 · MIT + file LICENSE

Description

Validates estimates of (conditional) average treatment effects obtained using observational data by a) making it easy to obtain and visualize estimates derived using a large variety of methods (G-computation, inverse propensity score weighting, etc.), and b) ensuring that estimates are easily compared to a gold standard (i.e., estimates derived from randomized controlled trials). 'RCTrep' offers a generic protocol for treatment effect validation based on four simple steps, namely, set-selection, estimation, diagnosis, and validation. 'RCTrep' provides a simple dashboard to review the obtained results. The validation approach is introduced by Shen, L., Geleijnse, G. and Kaptein, M. (2023) <doi:10.21203/rs.3.rs-2559287/v2>.

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies mvtnorm MatchIt ggplot2 ggpubr PSweight numDeriv R6 dplyr geex BART fastDummies tidyr copula shiny shinydashboard +2 more dependencies RCTrep

Version History

new 1.2.0 Mar 9, 2026