Packaged: Tue Jan  9 16:16:34 2007; snotman

Author: S. Van Buuren & C.G.M. Oudshoorn
Packaged: Thu Feb 19 14:22:54 2009; hornik

Author: Stef van Buuren <stef.vanbuuren@tno.nl> & Karin
Description: Multiple imputation of multivariate incomplete data by
Packaged: Tue Mar 17 09:11:32 2009; hornik

Description: Multiple Imputation using Fully Conditional Specification

Suggests: VIM, lattice, mitools, Zelig, nlme, lme4

Depends: R (>= 2.4.0), MASS, nnet, methods, lattice, stringr
Suggests: VIM, lattice, mitools, nlme, Zelig, lme4
Packaged: 2011-09-14 21:57:55 UTC; stefvanbuuren

Author: Stef van Buuren <stef.vanbuuren@tno.nl> & Karin Groothuis-Oudshoorn <c.g.m.oudshoorn@utwente.nl>
Depends: R (>= 2.4.0), MASS, nnet, methods, lattice
Packaged: 2011-11-21 20:40:32 UTC; stefvanbuuren

Depends: R (>= 2.10), MASS, nnet, lattice, methods
Suggests: VIM, mitools, nlme, Zelig, lme4, survival, gamlss
Packaged: 2012-03-25 19:29:14 UTC; stefvanbuuren

Package: mice
Type: Package
Version: 2.13
Title: Multivariate Imputation by Chained Equations
Date: 2012-06-30
Authors@R: c(person("Stef", "van Buuren", role = c("aut","cre"), email
= "stef.vanbuuren@tno.nl"), person("Karin",
"Groothuis-Oudshoorn", role = "aut", email =
"c.g.m.oudshoorn@utwente.nl"), person("Alexander", "Robitzsch",
role = "ctb", email = "a.robitzsch@bifie.at"),
person("Gerko","Vink", role = "ctb", email = "g.vink@uu.nl"))
Author: Stef van Buuren and Karin Groothuis-Oudshoorn, with
contributions from Alexander Robitzsch and Gerko Vink
Maintainer: Stef van Buuren <stef.vanbuuren@tno.nl>
Depends: R (>= 2.10), MASS, nnet, lattice, methods
Suggests: AGD, mitools, nlme, Zelig, lme4, survival, gamlss, pan, VIM
Description: Multiple imputation using Fully Conditional Specification
(FCS) implemented by the MICE algorithm. Each variable has its
own imputation model. Built-in imputation models are provided
for continuous data (predictive mean matching, normal), binary
data (logistic regression), unordered categorical data
(polytomous logistic regression) and ordered categorical data
(proportional odds). MICE can also impute continuous two-level
data (normal model, pan, second-level variables). Passive
imputation can be used to maintain consistency between
variables. Various diagnostic plots are available to inspect
the quality of the imputations.
License: GPL-2 | GPL-3
LazyLoad: yes
LazyData: yes
URL: http://www.stefvanbuuren.nl ; http://www.multiple-imputation.com
Packaged: 2012-07-03 21:09:11 UTC; stefvanbuuren
Repository: CRAN
Date/Publication: 2012-07-04 06:06:51