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rqlm (version 4.2-2)

Modified Poisson Regression for Binary Outcome and Related Methods Involving Target Trial Emulations

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. Also, standard computational tools for target trial emulation are included.

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Version

Install

install.packages('rqlm')

Monthly Downloads

495

Version

4.2-2

License

GPL-3

Maintainer

Hisashi Noma

Last Published

December 22nd, 2025

Functions in rqlm (4.2-2)

rqlm-package

The 'rqlm' package.
qesci.ls

Calculating confidence interval for modified least-squares regression based on the quasi-score test
qesci.pois

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

Calculating stabilized weights for IPW analysis: Longitudinal data
stabwtmulti

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

Calculating bootstrap confidence interval for modified least-squares regression based on the quasi-score statistic
exdata02

A simulated example dataset
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
coeff

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

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

Multiple imputation analysis for the generalized linear model
exdata01

A simulated example dataset
mch

A cluster-randomised trial dataset for the maternal and child health handbook
exdata03

A simulated example dataset with missing covariates
exdata04

A simulated example dataset for target trial emulation
rqlm

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

Calculating stabilized weights for IPW analysis: Single time point
ttemsm

Pooled logistic regression for target trial emulation