Installation
About
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:10.1080/00273171.2019.1640104doi: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.
Citation | mdmb citation info |
github.com/alexanderrobitzsch/mdmb | |
sites.google.com/site/alexanderrobitzsch2/software |
Key Metrics
Downloads
Yesterday | 40 +3% |
Last 7 days | 316 -24% |
Last 30 days | 1.256 +18% |
Last 90 days | 3.651 -47% |
Last 365 days | 18.317 -19% |