miceadds (3.4-17)

0 users

Some Additional Multiple Imputation Functions, Especially for 'mice'.

https://github.com/alexanderrobitzsch/miceadds
https://sites.google.com/site/alexanderrobitzsch2/software
http://cran.r-project.org/web/packages/miceadds

Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, ) are included. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, ), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, ; van Buuren, 2018, Ch.7, ), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, ) and substantive model compatible imputation (Bartlett et al., 2015, ).

Maintainer: Alexander Robitzsch
Author(s): Alexander Robitzsch [aut, cre], Simon Grund [aut], Thorsten Henke [aut]

License: GPL (>= 2)

Uses: mice, mitools, Rcpp, MBESS, car, coda, foreign, grouped, inline, lme4, numDeriv, sandwich, MCMCglmm, MASS, blme, CDM, sirt, TAM, BIFIEsurvey, readxl, mdmb, sjlabelled
Enhances: Amelia, pan, jomo, mitml, micemd
Reverse suggests: CDM, hot.deck, LSAmitR, mice, mitml, sirt, TAM

Released 7 days ago.


30 previous versions

Ratings

Overall:

  (0 votes)

Documentation:

  (0 votes)

Log in to vote.

Reviews

No one has written a review of miceadds 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 miceadds on google, google scholar, r-help, r-devel.

Visit miceadds on R Graphical Manual.