mdmb: Model Based Treatment of Missing Data

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>). T The regression model can be nonlinear (e.g., interaction quadratic effects or spline functions). Multilevel models with missing data in predictors is also available for Bayesian estimation. Substantive-model compatible multiple imputation can be also conducted.

Version: 0.8-47
Depends: R (≥ 3.1)
Imports: CDM, coda, graphics, MASS, miceadds (≥ 2.13-60), Rcpp, sirt, stats, TAM, utils
LinkingTo: miceadds, Rcpp, RcppArmadillo
Suggests: mice
Published: 2018-07-09
Author: Alexander Robitzsch [aut, cre], Oliver Luedtke [aut]
Maintainer: Alexander Robitzsch <robitzsch at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: mdmb citation info
Materials: README NEWS
CRAN checks: mdmb results


Reference manual: mdmb.pdf
Package source: mdmb_0.8-47.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: mdmb_0.8-47.tgz, r-oldrel: mdmb_0.8-47.tgz
Old sources: mdmb archive


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