print.risks

Print fitted risks model. The only change, compared to <code>print.glm()</code>,
is the addition of the main type of model: relative risk or risk difference.
If multiple models were fitted via <code>approach = "all"</code>, then the
first converged model will be printed.

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

print.risks function

<dl><dt>x</dt>
<dd>Fitted model</dd>
<dt>...</dt>
<dd>Passed to print.glm()</dd></dl>

Arguments

Print model — print.risks

<dl>

<dt>x</dt>
<dd>Fitted model</dd>


<dt>...</dt>
<dd>Passed to print.glm()</dd>

</dl>

print.risks: Print model

Description

Usage

Value

Arguments