RCTrep: Validation of Estimates of Treatment Effects in Observational Data

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>.

Package details

AuthorLingjie Shen [aut, cre, cph], Gijs Geleijnse [aut], Maurits Kaptein [aut]
MaintainerLingjie Shen <lingjieshen66@gmail.com>
LicenseMIT + file LICENSE
Version1.2.0
URL https://github.com/duolajiang/RCTrep
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("RCTrep")

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RCTrep documentation built on Nov. 2, 2023, 6:10 p.m.