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rqlm: Modified Poisson and Least-Squares Regressions for Binary Outcome

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. Also, 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>).

Version: 2.1-1
Depends: R (≥ 3.5.0)
Imports: stats, MASS, sandwich, mice
Published: 2024-05-23
DOI: 10.32614/CRAN.package.rqlm
Author: Hisashi Noma ORCID iD [aut, cre]
Maintainer: Hisashi Noma <noma at ism.ac.jp>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: rqlm results

Documentation:

Reference manual: rqlm.pdf

Downloads:

Package source: rqlm_2.1-1.tar.gz
Windows binaries: r-devel: rqlm_2.1-1.zip, r-release: rqlm_2.1-1.zip, r-oldrel: rqlm_2.1-1.zip
macOS binaries: r-release (arm64): rqlm_2.1-1.tgz, r-oldrel (arm64): rqlm_2.1-1.tgz, r-release (x86_64): rqlm_2.1-1.tgz, r-oldrel (x86_64): rqlm_2.1-1.tgz
Old sources: rqlm archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.