summary.risks

Determine type of risks model fitted and
generate appropriate summary.

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

risks

Estimate Risk Ratios and Risk Differences using Regression

Travis Gerke

summary.risks function

<dl><dt>object</dt>
<dd>Fitted model</dd>
<dt>conf.int</dt>
<dd>Add confidence intervals to printout? Defaults to TRUE.</dd>
<dt>default</dt>
<dd>Normal confidence intervals via confint.default()?
Default to TRUE. By setting <code>default = FALSE</code>, profiling-based
confidence intervals can be calculated for binomial models.</dd>
<dt>...</dt>
<dd>Passed on</dd></dl>

Arguments

Generate model summary — summary.risks

<dl>

<dt>object</dt>
<dd>Fitted model</dd>


<dt>conf.int</dt>
<dd>Add confidence intervals to printout? Defaults to TRUE.</dd>


<dt>default</dt>
<dd>Normal confidence intervals via confint.default()?
Default to TRUE. By setting <code>default = FALSE</code>, profiling-based
confidence intervals can be calculated for binomial models.</dd>


<dt>...</dt>
<dd>Passed on</dd>

</dl>

summary.risks: Generate model summary

Description

Usage

Value

Arguments

Details