Package: stdReg2 1.0.8

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.

Authors:Michael C Sachs [aut, cre], Arvid Sjölander [aut], Erin E Gabriel [aut], Johan Sebastian Ohlendorff [aut], Adam Brand [aut]

stdReg2_1.0.8.tar.gz
stdReg2_1.0.8.zip(r-4.7)stdReg2_1.0.8.zip(r-4.6)stdReg2_1.0.8.zip(r-4.5)
stdReg2_1.0.8.tgz(r-4.6-any)stdReg2_1.0.8.tgz(r-4.5-any)
stdReg2_1.0.8.tar.gz(r-4.7-any)stdReg2_1.0.8.tar.gz(r-4.6-any)
stdReg2_1.0.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
stdReg2/json (API)
NEWS

# Install 'stdReg2' in R:
install.packages('stdReg2', repos = c('https://sachsmc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sachsmc/stdreg2/issues

Pkgdown/docs site:https://sachsmc.github.io

Datasets:
  • clslowbwt - Birthweight data clustered on the mother.
  • singapore - Case-control study on oesophageal cancer in Chinese Singapore men.

On CRAN:

Conda:

5.72 score 5 stars 21 scripts 360 downloads 16 exports 11 dependencies

Last updated from:45899e4963. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK138
source / vignettesOK235
linux-release-x86_64OK149
macos-release-arm64OK101
macos-oldrel-arm64OK132
windows-develOK105
windows-releaseOK141
windows-oldrelOK113
wasm-releaseOK103

Exports:parfrailtyplot.std_glmplot.std_survprint.std_customprint.std_glmprint.std_survsandwichstandardizestandardize_coxphstandardize_geestandardize_glmstandardize_glm_drstandardize_levelstandardize_parfrailtysummary.parfrailtytidy

Dependencies:data.tabledrgeegenericslatticeMatrixnleqslvRcppRcppArmadillosandwichsurvivalzoo

Estimation of causal effects using stdReg2

Rendered fromoverview.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2024-09-04
Started: 2023-11-07

Implementing custom and new methods for standardization

Rendered fromcustom.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2025-03-21
Started: 2024-08-12

Readme and manuals

Help Manual

Help pageTopics
stdReg2: Regression Standardization for Causal InferencestdReg2-package stdReg2
Birthweight data clustered on the mother.clslowbwt
Fits shared frailty gamma-Weibull modelsparfrailty
Plots regression standardization fitplot.std_glm
Plots regression standardization fitplot.std_surv
Prints summary of regression standardization fitprint.std_custom print.std_glm print.std_surv
Print method for parametric frailty fitsprint.summary.parfrailty
Compute the sandwich variance components from a model fitsandwich
Case-control study on oesophageal cancer in Chinese Singapore men.singapore
Get standardized estimates using the g-formula with a custom modelstandardize
Regression standardization in Cox proportional hazards modelsstandardize_coxph
Regression standardization in conditional generalized estimating equationsstandardize_gee
Get regression standardized estimates from a glmstandardize_glm
Get regression standardized doubly-robust estimates from a glmstandardize_glm_dr
Get standardized estimates using the g-formula with and separate models for each exposure level in the datastandardize_level
Regression standardization in shared frailty gamma-Weibull modelsstandardize_parfrailty
Summarizes parfrailty fitsummary.parfrailty
Provide tidy output from a std_custom object for use in downstream computationstidy.std_custom
Provide tidy output from a std_glm object for use in downstream computationstidy.std_glm
Provide tidy output from a std_surv object for use in downstream computationstidy.std_surv