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>; 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.

Package details

Author Alexander Robitzsch [aut, cre], Oliver Luedtke [aut]
MaintainerAlexander Robitzsch <robitzsch@ipn.uni-kiel.de>
LicenseGPL (>= 2)
Version1.8-7
URL https://github.com/alexanderrobitzsch/mdmb https://sites.google.com/site/alexanderrobitzsch2/software
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("mdmb")

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mdmb documentation built on March 7, 2023, 6:58 p.m.