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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 "mdmb" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'mdmb: Model Based Treatment of Missing Data'
version: 1.10-1
doi: 10.32614/CRAN.package.mdmb
abstract: Contains model-based treatment of missing data for regression models with
  missing values in covariates or the dependent variable using maximum likelihood
  or Bayesian estimation (Ibrahim et al., 2005; <https://doi.org/10.1198/016214504000001844>;
  Luedtke, Robitzsch, & West, 2020a, 2020b; <https://doi.org/10.1080/00273171.2019.1640104><https://doi.org/10.1037/met0000233>).
  The regression model can be nonlinear (e.g., interaction effects, quadratic effects
  or B-spline functions). Multilevel models with missing data in predictors are available
  for Bayesian estimation. Substantive-model compatible multiple imputation can be
  also conducted.
authors:
- family-names: Robitzsch
  given-names: Alexander
  email: robitzsch@ipn.uni-kiel.de
- family-names: Luedtke
  given-names: Oliver
preferred-citation:
  type: manual
  title: 'mdmb: Model Based Treatment of Missing Data'
  authors:
  - family-names: Robitzsch
    given-names: Alexander
    email: robitzsch@ipn.uni-kiel.de
  - family-names: Luedtke
    given-names: Oliver
  year: '2024'
  notes: R package version 1.10-1
  url: https://CRAN.R-project.org/package=mdmb
  doi: 10.32614/CRAN.package.mdmb
repository: https://alexanderrobitzsch.r-universe.dev
repository-code: https://github.com/alexanderrobitzsch/mdmb
url: https://sites.google.com/view/alexander-robitzsch/software
date-released: '2024-07-15'
contact:
- family-names: Robitzsch
  given-names: Alexander
  email: robitzsch@ipn.uni-kiel.de