summary.riskdiff_iptw_result

Provides a comprehensive summary of IPTW risk difference analysis including
effect estimates, diagnostics, and interpretation guidance.

Calculates risk differences (or prevalence differences for
cross-sectional data) using generalized linear models with automatic
link function selection. Provides robust model fitting with fallback
methods, support for stratification and adjustment variables, inverse
probability of treatment weighting (IPTW) for causal inference, and
publication-ready output formatting. Handles model convergence issues
gracefully and provides confidence intervals using multiple approaches.
Methods are based on approaches described in Mark W. Donoghoe and
Ian C. Marschner (2018) "logbin: An R Package for Relative Risk
Regression Using the Log-Binomial Model" <doi:10.18637/jss.v086.i09>
for robust GLM fitting, Peter C. Austin (2011) "An Introduction to
Propensity Score Methods for Reducing the Effects of Confounding in
Observational Studies" <doi:10.1080/00273171.2011.568786> for IPTW methods,
and standard epidemiological methods for risk difference estimation as
described in Kenneth J. Rothman, Sander Greenland and Timothy L. Lash
(2008, ISBN:9780781755641) "Modern Epidemiology".

John D. Murphy

riskdiff

Risk Difference Estimation with Multiple Link Functions and
Inverse Probability of Treatment Weighting

summary.riskdiff_iptw_result function

<dl><dt>object</dt>
<dd>A riskdiff_iptw_result object</dd>
<dt>...</dt>
<dd>Additional arguments (currently ignored)</dd></dl>

Arguments

Summary Method for IPTW Risk Difference Results — summary.riskdiff_iptw_result

<dl>

<dt>object</dt>
<dd>A riskdiff_iptw_result object</dd>


<dt>...</dt>
<dd>Additional arguments (currently ignored)</dd>

</dl>

summary.riskdiff_iptw_result: Summary Method for IPTW Risk Difference Results

Description

Usage

Value

Arguments

Examples