-------------- MICE NEWS-------------------------------------------

MICE: Multivariate Imputation by Chained Equations

MICE is an R package implementing multiple imputation of
incomplete multivariate data according the principle of
Fully Conditional Specification (FCS).


The current version is MICE V2.3, which is described in

  Van Buuren S, Groothuis-Oudshoorn K (2010).
  MICE: Multivariate Imputation by Chained Equations in R.
  Journal of Statistical Software, forthcoming.
  http://www.stefvanbuuren.nl/publications/MICE in R - Draft.pdf


For more background on FCS see:

1)  Van Buuren S, Brand JPL, Groothuis-Oudshoorn CGM, Rubin DB (2006).
    Fully conditional specification in multivariate imputation,
    Journal of Statistical Computation and Simulation, 76(12),1049--1064.
    http://www.stefvanbuuren.nl/publications/FCS%20in%20multivariate%20imputation%20-%20JSCS%202006.pdf

2)  Van Buuren S (2007).
    Multiple imputation of discrete and continuous data by fully conditional specification
    Statistical Methods in Medical Research, 16(3), 219--242.
    http://www.stefvanbuuren.nl/publications/MI%20by%20FCS%20-%20SMMR%202007.pdf


More information and papers about MICE can be found in

http://www.multiple-imputation.com/


Question or suggestions about MICE can be send to

   stef.vanbuuren@tno.nl
or
   k.groothuis@rrd.nl


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CHANGELOG MICE
~~~~~~~~~~~~~~

V2.3 - 14-02-2010 / SvB

FIXED:   check.method: logicals are now treated as binary variables (Emmanuel Charpentier)
FIXED:   complete: the NULL imputation case is now properly handled
FIXED:   mice.impute.pmm: now creates between imputation variability for univariate predictor
FIXED:   remove.lindep: returns 'keep' vector instead of data 


V2.2 - 13-01-2010 / SvB

ADDED:   pool() now supports class 'multinom' (Jean-Baptiste Pingault)
FIXED:   bug fixed in check.data for data consisting of two columns (Rogier Donders, Thomas Koepsell)
ADDED:   new function remove.lindep() that removes predictors that are (almost) linearly dependent
FIXED:   bug fixed in pool() that produced an (innocent) warning message (Qi Zheng)

V2.1 - 14-09-2009 / SvB

ADDED:   pool() now also supports class 'mer'
CHANGED: nlme and lme4 are now only loaded if needed (by pool())
FIXED:   bug fixed in mice.impute.polyreg() when there was one missing entry (Emmanuel Charpentier)
FIXED:   bug fixed in plot.mids() when there was one missing entry (Emmanuel Charpentier) 
CHANGED: NAMESPACE expanded to allow easy access to function code
FIXED:   mice() can now find mice.impute.xxx() functions in the .GlobalEnv 


v2.0 - 26-08-2009 / SvB, KO 	Major upgrade for JSS manuscript

ADDED:   new functions cbind.mids(), rbind.mids(), ibind()
ADDED:   new argument in mice(): 'post' in post-processing imputations
ADDED:   new functions: pool.scaler(), pool.compare(), pool.r.squared()
ADDED:	 new data: boys, popmis, windspeed
FIXED:	 function summary.mipo all(object$df) command fixed
DELETED: data.frame.to.matrix replaced by the internal data.matrix function
ADDED:   new imputation method mice.impute.2l.norm() for multilevel data
CHANGED: pool now works for any class having a vcov() method
ADDED:   with.mids() provides a general complete-data analysis
ADDED:   type checking in mice() to ensure appropriate imputation methods
ADDED:   warning added in mice() for constant predictors
ADDED:   prevention of perfect prediction in mice.impute.logreg() and mice.impute.polyreg()
CHANGED: mice.impute.norm.improper() changed into mice.impute.norm.nob()
DELETED: mice.impute.polyreg2() deleted
ADDED:   new 'include' argument in complete()
ADDED:   support for the empty imputation method in mice()
ADDED:   new function md.pairs()
ADDED:   support for intercept imputation
ADDED:   new function quickpred()
FIXED:   plot.mids() bug fix when number of variables > 5


v1.21 - 15/3/2009 SvB  Maintainance release

FIXED:   Stricter type checking on logicals in mice() to evade warnings.
CHANGED: Modernization of all help files.
FIXED:   padModel: treatment changed to contr.treatment
CHANGED: Functions check.visitSequence, check.predictorMatrix, check.imputationMethod are now coded as local to mice()
FIXED:   existsFunction in check.imputationMethod now works both under S-Plus and R

v1.16 - 6/25/2007

FIXED: The impution function impute.logreg used convergence criteria that were too optimistic when fitting a GLM with glm.fit. Thanks to Ulrike Gromping (groemping@tfh-berlin.de).

v1.15 - 01/09/2006

Release Notes & known issues:
* Work is underway to completely rewrite the library, including imputation functions for multilevel models

FIXED: In the lm.mids and glm.mids functions, parameters were not passed through to glm and lm.

v1.14R - 9/26/2005 11:44AM

Release Notes & known issues:
* Although MICE will remain compatible with S-PLUS, because of its superior memory management we encourage the use of R for multiple imputation with MICE.
* Imputation functions 'impute.norm.improper' and 'impute.logreg2' are disabled.

FIXED: Passive imputation works again. (Roel de Jong)
CHANGED: Random seed is now left alone, UNLESS the argument "seed" is specified. This means that unless you
specify identical seed values, imputations of the same dataset will be different for multiple calls to mice. (Roel de Jong)
FIXED (docs): Documentation for "impute.mean" (Roel de Jong)
FIXED: Function 'summary.mids' now works (Roel de Jong)
FIXED: Imputation function 'impute.polyreg' and 'impute.lda' should now work under R

v1.13
Changed function checkImputationMethod, Feb 6, 2004

v1.12
Maintainance, S-Plus 6.1 and R 1.8 unicode, January 2004

v1.1
R version (with help of Peter Malewski and Frank Harrell), Feb 2001

v1.0
Original S-PLUS release, June 14 2000