Package: mdmb
Type: Package
Title: Model Based Treatment of Missing Data
Version: 0.8-47
Date: 2018-07-09 18:39:51
Author: 
    Alexander Robitzsch [aut, cre], Oliver Luedtke [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>
Description: 
    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.
Depends: R (>= 3.1)
Imports: CDM, coda, graphics, MASS, miceadds (>= 2.13-60), Rcpp, sirt,
        stats, TAM, utils
Suggests: mice
LinkingTo: miceadds, Rcpp, RcppArmadillo
URL: https://github.com/alexanderrobitzsch/mdmb,
        https://sites.google.com/site/alexanderrobitzsch2/software
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2018-07-09 16:40:27 UTC; sunpn563
Repository: CRAN
Date/Publication: 2018-07-09 17:10:03 UTC
