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rqlm (version 4.3-1)

Modified Poisson Regression for Binary Outcome and Related Methods

Description

Modified Poisson, logistic and least-squares regression analyses for binary outcomes of Zou (2004) , Noma (2025), and Cheung (2007) 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.

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Version

Install

install.packages('rqlm')

Monthly Downloads

365

Version

4.3-1

License

GPL-3

Maintainer

Hisashi Noma

Last Published

January 28th, 2026

Functions in rqlm (4.3-1)

ttemsm

Pooled logistic regression for target trial emulation
exdata03

A simulated example dataset with missing covariates
exdata04

A simulated example dataset for target trial emulation
qesci.pois

Calculating confidence interval for modified Poisson regression based on the quasi-score test
SumStat

Creating summary table for IPTW analysis using stabilized weights
bsci.ls

Calculating bootstrap confidence interval for modified least-squares regression based on the quasi-score statistic
rqlm-package

The 'rqlm' package.
qlogist

Augmented (modified) logistic regression analyses for estimating risk ratio
mi_rqlm

Multiple imputation analysis for modified Poisson and least-squares regressions
bsci.pois

Calculating bootstrap confidence interval for modified Poisson regression based on the quasi-score statistic
qesci.ls

Calculating confidence interval for modified least-squares regression based on the quasi-score test
exdata01

A simulated example dataset
mi_glm

Multiple imputation analysis for the generalized linear model
exdata02

A simulated example dataset
stabwtmulti

Calculating stabilized weights for IPW analysis: Single time point (for more than 3 groups)
coeff

Computation of the ordinary confidence intervals and P-values using the model variance estimator
mch

A cluster-randomised trial dataset for the maternal and child health handbook
rqlm

Modified Poisson and least-squares regression analyses for binary outcomes
stabwt

Calculating stabilized weights for IPW analysis: Single time point
stabwtlong

Calculating stabilized weights for IPW analysis: Longitudinal data