Modified Poisson Regression for Binary Outcome and Related Methods
Overview
Modified Poisson, logistic and least-squares regression analyses for binary outcomes of Zou (2004) doi:10.1093/aje/kwh090, Noma (2026)doi:10.1016/j.spl.2026.110698, 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.
- Added generic coef(), vcov(), and family() methods for improved interoperability with other R packages.
- Added cluster-robust ID support to rqlm() and qlogist().
- The ttemsm() function now returns the full covariance matrix and fitted glm object, and uses uniform weights when weight is omitted.
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- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK13 OK2026-05-02
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- ERROR11 OK, 1 ERROR2026-04-25
- OK14 OK2026-03-10
Documentation
- Help pages
- 23 (1 internal)includes a package overview page
- Examples that run
- 100%16 run in a plain check
- Exported functions with examples
- 93%
- Documented parameters
- 99%
- Return-value docs
- 100%
- Help pages citing references
- 74%
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- RR 4.5.0 released · 2025-04-11
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- 1.1-12024-01-11
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2024-01-11
- Total releases
- 14 / 2 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 132 KB / 7 files
- Download size
- 158 KB
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