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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "glmfitmiss" in publications use:'
type: software
license: MIT
title: 'glmfitmiss: Fitting GLMs with Missing Data in Both Responses and Covariates'
version: 2.1.0
doi: 10.32614/CRAN.package.glmfitmiss
abstract: 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) <https://doi.org/10.1111/j.1541-0420.2008.01186.x>,
  Maity, Pradhan, and Das (2019) <https://doi.org/10.1080/00031305.2017.1407359> for
  further methodological details.
authors:
- family-names: Pradhan
  given-names: Vivek
  email: vpradhan2009@gmail.com
- family-names: Nychka
  given-names: Douglas
  email: nychka@mines.edu
- family-names: Bandyopadhyay
  given-names: Soutir
  email: bsoutir@gmail.com
repository: https://cran.r-universe.dev
commit: d0ff6accd96439a8d204523285711e2ffdd967af
date-released: '2025-04-22'
contact:
- family-names: Pradhan
  given-names: Vivek
  email: vpradhan2009@gmail.com