stdReg2: Regression Standardization for Causal Inference

Contains more modern tools for causal inference using regression standardization. Four general classes of models are implemented; generalized linear models, conditional generalized estimating equation models, Cox proportional hazards models, and shared frailty gamma-Weibull models. Methodological details are described in Sjölander, A. (2016) <doi:10.1007/s10654-016-0157-3>. Also includes functionality for doubly robust estimation for generalized linear models in some special cases, and the ability to implement custom models.

Version:	1.0.1
Depends:	R (≥ 2.10)
Imports:	data.table, drgee, generics, survival
Suggests:	causaldata, AF, knitr, nnet, rmarkdown, testthat (≥ 3.0.0)
Published:	2024-09-13
DOI:	10.32614/CRAN.package.stdReg2
Author:	Michael C Sachs [aut, cre], Arvid Sjölander [aut], Erin E Gabriel [aut], Johan Sebastian Ohlendorff [aut], Adam Brand [aut]
Maintainer:	Michael C Sachs <sachsmc at gmail.com>
BugReports:	https://github.com/sachsmc/stdReg2/issues/
License:	AGPL (≥ 3)
URL:	https://sachsmc.github.io/stdReg2/
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	stdReg2 results

Documentation:

Reference manual:	stdReg2.pdf
Vignettes:	Implementing custom and new methods for standardization (source, R code) Estimation of causal effects using stdReg2 (source, R code)

Downloads:

Package source:	stdReg2_1.0.1.tar.gz
Windows binaries:	r-devel: stdReg2_1.0.1.zip, r-release: stdReg2_1.0.1.zip, r-oldrel: stdReg2_1.0.1.zip
macOS binaries:	r-release (arm64): stdReg2_1.0.1.tgz, r-oldrel (arm64): stdReg2_1.0.1.tgz, r-release (x86_64): stdReg2_1.0.1.tgz, r-oldrel (x86_64): stdReg2_1.0.1.tgz

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