confint.duplicate

Estimate confidence intervals for the case duplication model
with robust/sandwich/empirical covariance structure.

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

confint.duplicate function

<dl><dt>object</dt>
<dd>Fitted model</dd>
<dt>parm</dt>
<dd>Not used</dd>
<dt>level</dt>
<dd>Confidence level, defaults to 0.95</dd>
<dt>...</dt>
<dd>Additional arguments, not used</dd></dl>

Arguments

Clustering-corrected confidence intervals for case duplication model — confint.duplicate

<dl>

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


<dt>parm</dt>
<dd>Not used</dd>


<dt>level</dt>
<dd>Confidence level, defaults to 0.95</dd>


<dt>...</dt>
<dd>Additional arguments, not used</dd>

</dl>

confint.duplicate: Clustering-corrected confidence intervals for case duplication model

Description

Usage

Value

Arguments