https://github.com/cran/mdmb
Tip revision: 8324acb4f0fe0eb205459e6d3622f88e8627818f authored by Alexander Robitzsch on 28 February 2023, 21:02:29 UTC
version 1.8-7
version 1.8-7
Tip revision: 8324acb
DESCRIPTION
Package: mdmb
Type: Package
Title: Model Based Treatment of Missing Data
Version: 1.8-7
Date: 2023-02-28 22:35:18
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>;
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.
Depends: R (>= 3.1)
Imports: CDM, coda, graphics, miceadds (>= 3.2-23), Rcpp, sirt, stats,
utils
Suggests: MASS
LinkingTo: miceadds, Rcpp, RcppArmadillo
Enhances: JointAI, jomo, mice, smcfcs
URL: https://github.com/alexanderrobitzsch/mdmb,
https://sites.google.com/site/alexanderrobitzsch2/software
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2023-02-28 21:36:48 UTC; sunpn563
Repository: CRAN
Date/Publication: 2023-02-28 22:02:29 UTC