Model Based Treatment of Missing Data R package mdmb version 1.9-22 CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData) CRAN Task View: MixedModels (https://CRAN.R-project.org/view=MixedModels) 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; <doi:10.1198/016214504000001844>; Luedtke, Robitzsch, & West, 2020a, 2020b; <doi:10.1080/00273171.2019.1640104><doi: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. Software Depends: R (>= 3.1) Imports: CDM, coda, graphics, miceadds (>= 3.2-23), Rcpp, sirt, stats, utils LinkingTo: miceadds, Rcpp, RcppArmadillo Suggests: MASS Enhances: JointAI, jomo, mice, smcfcs Alexander Robitzsch <robitzsch@ipn.uni-kiel.de> Comprehensive R Archive Network (CRAN) Alexander Robitzsch [aut, cre], Oliver Luedtke [aut] GPL (>= 2) 2024-07-15 application/tgz https://CRAN.R-project.org/package=mdmb doi:10.32614/CRAN.package.mdmb