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rqlm  

Modified Poisson and Least-Squares Regressions for Binary Outcome
View on CRAN: Click here


Download and install rqlm package within the R console
Install from CRAN:
install.packages("rqlm")

Install from Github:
library("remotes")
install_github("cran/rqlm")

Install by package version:
library("remotes")
install_version("rqlm", "2.1-1")



Attach the package and use:
library("rqlm")
Maintained by
Hisashi Noma
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-01-11
Latest Update: 2024-01-19
Description:
Modified Poisson and least-squares regression analyses for binary outcomes of Zou (2004) 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. 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) ).
How to cite:
Hisashi Noma (2024). rqlm: Modified Poisson and Least-Squares Regressions for Binary Outcome. R package version 2.1-1, https://cran.r-project.org/web/packages/rqlm. Accessed 21 Dec. 2024.
Previous versions and publish date:
1.1-1 (2024-01-11 10:50), 1.2-1 (2024-01-19 10:50), 1.3-1 (2024-05-17 16:40)
Other packages that cited rqlm R package
View rqlm citation profile
Other R packages that rqlm depends, imports, suggests or enhances
Complete documentation for rqlm
Functions, R codes and Examples using the rqlm R package
Some associated functions: bsci.ls . bsci.pois . exdata01 . exdata02 . qesci.ls . qesci.pois . rqlm-package . rqlm . 
Some associated R codes: Full rqlm package functions and examples
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