summary.margstd_delta

Summary for models using marginal standardization with delta method SEs

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.margstd_delta function

<dl><dt>object</dt>
<dd>Model</dd>
<dt>dispersion</dt>
<dd>Not used</dd>
<dt>correlation</dt>
<dd>Not used</dd>
<dt>symbolic.cor</dt>
<dd>Not used</dd>
<dt>level</dt>
<dd>Confidence level, defaults to <code>0.95</code>.</dd>
<dt>...</dt>
<dd>Not used</dd></dl>

Arguments

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

<dl>

<dt>object</dt>
<dd>Model</dd>


<dt>dispersion</dt>
<dd>Not used</dd>


<dt>correlation</dt>
<dd>Not used</dd>


<dt>symbolic.cor</dt>
<dd>Not used</dd>


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


<dt>...</dt>
<dd>Not used</dd>

</dl>

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

Description

Usage

Value

Arguments