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glmfitmiss  

Fitting GLMs with Missing Data in Both Responses and Covariates
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("glmfitmiss", "2.1.0")



Attach the package and use:
library("glmfitmiss")
Maintained by
Vivek Pradhan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-04-22
Latest Update: 2025-04-22
Description:
Fits generalized linear models (GLMs) when there is missing data in both the response and categorical covariates. The functions implement likelihood-based methods using the Expectation and Maximization (EM) algorithm and optionally apply Firth’s bias correction for improved inference. See Pradhan, Nychka, and Bandyopadhyay (2025) <https:>, Maiti and Pradhan (2009) <doi:10.1111/j.1541-0420.2008.01186.x>, Maity, Pradhan, and Das (2019) <doi:10.1080/00031305.2017.1407359> for further methodological details.
How to cite:
Vivek Pradhan (2025). glmfitmiss: Fitting GLMs with Missing Data in Both Responses and Covariates. R package version 2.1.0, https://cran.r-project.org/web/packages/glmfitmiss. Accessed 13 Mar. 2026.
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