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>.
Version: 1.2.0 Depends: R (≥ 2.10), base Imports: mvtnorm, MatchIt, ggplot2, ggpubr, PSweight, numDeriv, R6, dplyr, geex, BART, fastDummies, tidyr, copula, shiny, shinydashboard, glue, stats, utils, caret Suggests: rmarkdown, knitr, testthat (≥ 3.0.0) Published: 2023-11-02 DOI: 10.32614/CRAN.package.RCTrep Author: Lingjie Shen [aut, cre, cph], Gijs Geleijnse [aut], Maurits Kaptein [aut] Maintainer: Lingjie Shen <lingjieshen66 at gmail.com> License: MIT + file LICENSE URL: https://github.com/duolajiang/RCTrep NeedsCompilation: no Citation: RCTrep citation info Materials: README NEWS CRAN checks: RCTrep results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=RCTrep to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4