print.nnt_iptw_result

Calculates risk differences (or prevalence differences for
cross-sectional data) and Number Needed to Treat (NNT) 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 with NNT calculations, 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

print.nnt_iptw_result function

<dl><dt>x</dt>
<dd>An nnt_iptw_result object from calc_risk_diff_iptw(..., nnt = TRUE)</dd>
<dt>digits</dt>
<dd>Number of decimal places for NNT estimates (default: 1)</dd>
<dt>...</dt>
<dd>Additional arguments (ignored)</dd></dl>

Arguments

Print Method for IPTW NNT Results — print.nnt_iptw_result

<dl>

<dt>x</dt>
<dd>An nnt_iptw_result object from calc_risk_diff_iptw(..., nnt = TRUE)</dd>


<dt>digits</dt>
<dd>Number of decimal places for NNT estimates (default: 1)</dd>


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

</dl>

print.nnt_iptw_result: Print Method for IPTW NNT Results

Description

Usage

Arguments