mdmb
R package 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.
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References in zbMATH (referenced in 2 articles )
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Sorted by year (- Erler, N. S., Rizopoulos, D., Lesaffre, E. M. E. H.: JointAI: Joint Analysis and Imputation of Incomplete Data in R (2021) not zbMATH
- Sheikhi, Ayyub; Arabpour, Alireza; Khosravi, Mohsen; Mashinchi, Mashallah; Pourmousa, Reza; Rezapour, Mohsen; Roastami, Mohammad Javad; Nejad, Amin Abbdollah; Badakhshan, Abed: On hierarchical multiple imputation method for handling missing data (2021)