Package: hettx 0.1.3

hettx: Fisherian and Neymanian Methods for Detecting and Measuring Treatment Effect Variation

Implements methods developed by Ding, Feller, and Miratrix (2016) <doi:10.1111/rssb.12124> <arxiv:1412.5000>, and Ding, Feller, and Miratrix (2018) <doi:10.1080/01621459.2017.1407322> <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.

Authors:Peng Ding [aut], Avi Feller [aut], Ben Fifield [aut, cre], Luke Miratrix [aut]

hettx_0.1.3.tar.gz
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hettx.pdf |hettx.html
hettx/json (API)

# Install 'hettx' in R:
install.packages('hettx', repos = c('https://bfifield.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/bfifield/hettx/issues

Datasets:

On CRAN:

24 exports 9 stars 1.47 score 50 dependencies 21 scripts 251 downloads

Last updated 1 years agofrom:fe19452cd9. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 12 2024
R-4.5-winOKSep 12 2024
R-4.5-linuxOKSep 12 2024
R-4.4-winOKSep 12 2024
R-4.4-macOKSep 12 2024
R-4.3-winOKSep 12 2024
R-4.3-macOKSep 12 2024

Exports:detect_idiosyncraticestimate_systematicget.p.valueKS.statmake.linear.datamake.quadradic.datamake.randomized.compliance.datmake.randomized.datmake.skew.dataR2rq.statrq.stat.cond.covrq.stat.uncond.covSESKS.pool.tSKS.statSKS.stat.covSKS.stat.cov.poolSKS.stat.cov.rqSKS.stat.int.covSKS.stat.int.cov.pooltest.stat.infovariance.ratio.testWSKS.t

Dependencies:clicodetoolscolorspacecpp11doParalleldplyrfansifarverforeachformula.toolsgenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmgcvmomentsmunsellmvtnormnlmeoperator.toolspillarpkgconfigplyrpurrrquantregR6RColorBrewerRcpprlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

detect_idiosyncratic() Tutorial

Rendered fromdetect_idiosyncratic_vignette.Rmdusingknitr::rmarkdownon Sep 12 2024.

Last update: 2023-02-16
Started: 2019-01-21

Tutorial on Systematic Treatment Detection

Rendered fromestimate_systematic_vignette.Rmdusingknitr::rmarkdownon Sep 12 2024.

Last update: 2019-02-08
Started: 2019-01-21