risks

The risks package allows for fitting risk ratio and risk difference
models using regression.

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,
<doi:10.1002/sim.4780121808>), log-binomial (Poisson) models with empirical
variance (Zou 2004, <doi:10.1093/aje/kwh090>), binomial models with starting
values from Poisson models (Spiegelman and Hertzmark 2005,
<doi:10.1093/aje/kwi188>), and others.

Konrad Stopsack

Estimate Risk Ratios and Risk Differences using Regression

Travis Gerke

risks function

<code>riskratio</code>: Fit risk ratio models.
<code>riskdiff</code>: Fit risk difference models.
<code>summary.risks</code>: Summarize fitted model.
<code>tidy.risks</code>: Tibble (data frame) of parameters,
coefficients, standard errors, confidence intervals.
<code>confint.robpoisson</code>,
<code>confint.duplicate</code>,
<code>confint.margstd_boot</code>,
<code>confint.margstd_delta</code>: Confidence intervals. (Standard
confidence intervals for generalized linear models are used for other
models.)

risks functions

risks: Estimate risk ratios and risk differences using regression — risks

<code>riskratio</code>: Fit risk ratio models.
<code>riskdiff</code>: Fit risk difference models.
<code>summary.risks</code>: Summarize fitted model.
<code>tidy.risks</code>: Tibble (data frame) of parameters,
coefficients, standard errors, confidence intervals.
<code>confint.robpoisson</code>,
<code>confint.duplicate</code>,
<code>confint.margstd_boot</code>,
<code>confint.margstd_delta</code>: Confidence intervals. (Standard
confidence intervals for generalized linear models are used for other
models.)

risks: risks: Estimate risk ratios and risk differences using regression

Description

Arguments

risks functions

See Also