doi:10.1111/rssb.12124> <doi:10.48550/arXiv.1412.5000>, and Ding, Feller, and Miratrix (2018) <doi:10.1080/01621459.2017.1407322> <doi:10.48550/arXiv.1605.06566> for testing whether there is unexplained variation in treatment effects across observations, and for characterizing the extent of the explained and unexplained variation in treatment effects. The package includes wrapper functions implementing the proposed methods, as well as helper functions for analyzing and visualizing the results of the test.">

hettx: Fisherian and Neymanian Methods for Detecting and Measuring Treatment Effect Variation (original) (raw)

Implements methods developed by Ding, Feller, and Miratrix (2016) <doi:10.1111/rssb.12124> <doi:10.48550/arXiv.1412.5000>, and Ding, Feller, and Miratrix (2018) <doi:10.1080/01621459.2017.1407322> <doi:10.48550/arXiv.1605.06566> for testing whether there is unexplained variation in treatment effects across observations, and for characterizing the extent of the explained and unexplained variation in treatment effects. The package includes wrapper functions implementing the proposed methods, as well as helper functions for analyzing and visualizing the results of the test.

Version: 0.1.3
Depends: R (≥ 2.14.0)
Imports: quantreg, plyr, mvtnorm, MASS, foreach, parallel, doParallel, moments, formula.tools, purrr, dplyr, ggplot2, tidyr
Suggests: testthat, knitr, rmarkdown
Published: 2023-08-19
DOI: 10.32614/CRAN.package.hettx
Author: Peng Ding [aut], Avi Feller [aut], Ben Fifield [aut, cre], Luke Miratrix [aut]
Maintainer: Ben Fifield
BugReports: https://github.com/bfifield/hettx/issues
License: GPL (≥ 3)
NeedsCompilation: no
In views: CausalInference
CRAN checks: hettx results

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