mdmb (1.3-18)

0 users

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; ). 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.

Maintainer: Alexander Robitzsch
Author(s): Alexander Robitzsch [aut, cre], Oliver Luedtke [aut]

License: GPL (>= 2)

Uses: CDM, coda, miceadds, Rcpp, sirt, MASS
Enhances: mice, jomo, smcfcs, JointAI
Reverse suggests: miceadds

Released 7 months ago.

14 previous versions



  (0 votes)


  (0 votes)

Log in to vote.


No one has written a review of mdmb yet. Want to be the first? Write one now.

Related packages: Amelia, CVThresh, HardyWeinberg, Hmisc, ade4, cat, eigenmodel, experiment, ltm, memisc, mice, mitools, mix, norm, pan, randomForest, sbgcop, yaImpute, zoo, SNPassoc(20 best matches, based on common tags.)

Search for mdmb on google, google scholar, r-help, r-devel.

Visit mdmb on R Graphical Manual.