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risks (version 0.4.2)

Estimate Risk Ratios and Risk Differences using Regression

Description

Risk ratios and risk differences are estimated using regression models that allow for binary, categorical, and continuous exposures and confounders. Implemented are marginal standardization after fitting logistic models (g-computation) with delta-method and bootstrap standard errors, Miettinen's case-duplication approach (Schouten et al. 1993, ), log-binomial (Poisson) models with empirical variance (Zou 2004, ), binomial models with starting values from Poisson models (Spiegelman and Hertzmark 2005, ), and others.

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Version

Install

install.packages('risks')

Monthly Downloads

257

Version

0.4.2

License

GPL-3

Maintainer

Konrad Stopsack

Last Published

June 13th, 2023

Functions in risks (0.4.2)

riskratio

Fit risk ratio and risk difference models
summary.margstd_boot

Summary for models using marginal standardization
conv.test

Helper function for logbin and addreg packages
rr_rd_mantel_haenszel

Risk Ratios and Risk Differences from Mantel-Haenszel Estimators
summary.margstd_delta

Summary for models using marginal standardization with delta method SEs
confint.margstd_delta

Delta method confidence intervals
risks

risks: Estimate risk ratios and risk differences using regression
breastcancer

Breast Cancer Data
summary.duplicate

Summary for logistic model with case duplication and cluster-robust covariance
summary.robpoisson

Summary for Poisson model with robust covariance
summary.risks

Generate model summary
confint.duplicate

Clustering-corrected confidence intervals for case duplication model
tidy.risks

Tidy model summaries for risks models
confint.robpoisson

Robust confidence intervals for Poisson model
print.risks

Print model
confint.margstd_boot

Bootstrap confidence intervals
print.summary.risks

Print model summary