Package: mdmb
Type: Package
Title: Model Based Treatment of Missing Data
Version: 1.2-4
Date: 2019-01-11 11:17:36
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>).
    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.
Depends: R (>= 3.1)
Imports: CDM (>= 7.1-2), coda, graphics, MASS, miceadds (>= 2.13-60),
        Rcpp, sirt, stats, 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: 2019-01-11 10:19:02 UTC; sunpn563
Repository: CRAN
Date/Publication: 2019-01-11 12:20:03 UTC
