exdata03

A simulated cohort data with binomial outcome. Some covariates involve missing data.<ul>
<li><code>y</code>: Dichotomous outcome variable.</li>
<li><code>x1</code>: Continuous covariate.</li>
<li><code>x2</code>: Binary covariate.</li>
<li><code>x3</code>: Binary covariate.</li>
<li><code>x4</code>: Binary covariate.</li>
</ul>

datasets

Modified Poisson and least-squares regression analyses for binary outcomes of Zou (2004) <doi:10.1093/aje/kwh090> and Cheung (2007) <doi:10.1093/aje/kwm223> have been standard multivariate analysis methods to estimate risk ratio and risk difference in clinical and epidemiological studies. This R package involves an easy-to-handle function to implement these analyses by simple commands. Missing data analysis tools (multiple imputation) are also involved. In addition, recent studies have shown the ordinary robust variance estimator possibly has serious bias under small or moderate sample size situations for these methods. This package also provides computational tools to calculate alternative accurate confidence intervals (Noma and Gosho (2024) <Forthcoming>).

Hisashi Noma

rqlm

Modified Poisson and Least-Squares Regressions for Binary
Outcome and Their Generalizations

exdata03 function

A simulated cohort data with binomial outcome (n=1200). Some covariates involve missing data.

exdata03: A simulated example dataset with missing covariates

Description

Usage

Arguments

Format