mice 3.11.0

Major changes

• The Cox model does not return df.residual, which caused problematic behavior in the D1(), D2(), D3(), anova() and pool(). mice now extracts the relevant information from other parts of the objects returned by survival::coxph(), which solves long-standing issues with the integration of the Cox model (#246).
• Adds missing Rccp dependency to work with tidyr 1.1.1 (#248).

Minor changes

• Addresses warnings: Non-file package-anchored link(s) in documentation object.
• Updates on ampute documentation (#251).
• Ask user permission before installing a package from suggests.

mice 3.10.0

Major changes

• New functions tidy.mipo() and glance.mipo() return standardized output that conforms to broom specifications. Kindly contributed by Vincent Arel Bundock (#240).

Minor changes

• Solves a problem with the D3 testing script that produced an error on CRAN (#244).

mice 3.9.0

Major changes

• The D3() function in mice gave incorrect results. This version solves a problem in the calculation of the D3-statistic. See #226 and #228 for more details. The documentation explains why results from mice::D3() and mitml::testModels() may differ.
• The pool() function is now more forgiving when there is no glance() function (#233)
• It is possible to bypass remove.lindep() by setting eps = 0 (#225)

Minor changes

• Adds reference to Leacy’s thesis
• Adds an example to the plot.mids() documentation

mice 3.8.0

Major changes

• This version adds two new NARFCS methods for imputing data under the Missing Not at Random (MNAR) assumption. NARFCS is generalised version of the so-called \(\delta\)-adjustment method. Margarita Moreno-Betancur and Ian White kindly contributes the functions mice.impute.mnar.norm() and mice.impute.mnar.logreg(). These functions aid in performing sensitivity analysis to investigate the impact of different MNAR assumptions on the conclusion of the study. An alternative for MNAR is the older mice.impute.ri() function.
• Installation of mice is faster. External packages needed for imputation and analyses are now installed on demand. The number of dependencies as estimated by rsconnect::appDepencies() decreased from 132 to 83.
• The name clash with the complete() function of tidyr should no longer be a problem.
• There is now a more flexible pool() function that integrates better with the broom and broom.mixed packages.

Bug fixes

• Deprecates pool.compare(). Use D1() instead (#220)
• Removes everything in utils::globalVariables()
• Prevents name clashes with tidyr by defining complete.mids() as an S3 method for the tidyr::complete() generic (#212)
• Extends the pool() function to deal with multiple sets of parameters. Currently supported keywords are: term (all broom functions), component (some broom.mixed functions) and y.values (for multinom() model) (#219)
• Adds a new install.on.demand() function for lighter installation
• Adds toenail2 and remove dependency on HSAUR3
• Solves problem with ampute in extreme cases (#216)
• Solves problem with pool with mgcv::gam (#218)
• Adds .gitattributes for consistent line endings

mice 3.7.0

• Solves a bug that made polr() always fail (#206)
• Aborts if one or more columns are a data.frame (#208)
• Update mira-class documentation (#207)
• Remove links to deprecated package CALIBERrfimpute
• Adds check on partial missing level-2 data to 2lonly.norm and 2lonly.pmm
• Change calculation of a2 to elementwise division by a matrix of observations
• Extend documentation for 2lonly.norm and 2lonly.pmm
• Repair return value from 2lonly.pmm
• Imputation method 2lonly.mean now also works with factors
• Replace deprecated imputationMethod argument in examples by method
• More informative error message when stopped after pre-processing (#194)
• Updated URL’s in DESCRIPTION
• Fix string matching in check.predictorMatrix() (#191)

mice 3.6.0

• Copy toenail data from orphaned DPpackage package
• Remove DPpackage from Suggests field in DESCRIPTION
• Adds support for rotated names in md.pattern() (#170, #177)

mice 3.5.0

• This version has some error fixes
• Fixes a bug in the sampler that ignored imputed values in variables outside the active block (#175, @alexanderrobitzsch)
• Adds a note to the documenation of as.mids() (#173)
• Removes a superfluous warning from process_mipo() (#92)
• Fixes an error in the degrees of freedom of the P-value calculation (#171)

mice 3.4.0

• Add a hex sticker to the mice package. Designed by Jaden M. Walters.
• Specify the R3.5.0 random generator in order to pass CRAN tests
• Remove test-fix.coef.R from tests
• Adds a rotate.names argument to md.pattern() (#154, #160)
• Fix to solve the name-matching problem (#156, #149, #147)
• Fix that removes the pre-check for existence of mice.impute.xxx() so that mice::mice() works as expected (#55)
• Solves a bug that crashed mids2spss(), thanks Edgar Schoreit (#149)
• Solves a problem in the routing logic (#149) causing that passive imputation was not done when no predictors were specified. No passive imputation correctly will ignore any the specification of predictorMatrix.
• Implements an alternative solution for #93 and #96. Instead of skipping imputation of variables without predictors, mice 3.3.1 will impute those variables using the intercept only
• Adds a routine contributed by Simon Grund that checks for deprecated arguments #137
• Improves the nelsonaalen() function for data where variables time or status have already been defined (#140), thanks matthieu-faron

mice 3.3.0

• Solves bug in passive imputation (#130). Warning: This bug may have caused invalid imputations in mice 3.0.0 - mice 3.2.0 under passive imputation.
• Updates code to broom 0.5.0 (#128)
• Solves problem with mice.impute.2l.norm() (#129)
• Use explicit foreign function calls in tests

mice 3.2.0

• Skip tests for mice.impute.2l.norm() (#129)
• Skip tests for D1() (#128)
• Solve problem with md.pattern (#126)
• Evades warning in rbind and cbind (#114)
• Solves rbind problem when method is a list (#113)
• More efficient use of parlmice (#109)
• Add dfcom argument to pool() (#105, #110)
• Updates to parlmice + bugfix (#107)

mice 3.1.0

• New parallel functionality: parlmice (#104)
• Incorporate suggestion of @JoergMBeyer to flux (#102)
• Replace duplicate code by estimice (#101)
• Better checking for empty methods (#99)
• Remove problem with parent.frame (#98)
• Set empty method for complete data (#93)
• Add NEWS.md, index.Rmd and online package documentation
• Track .R instead of .r
• Patch issue with updateLog (#8, @alexanderrobitzsch)
• Extend README
• Repair issue md.pattern (#90)
• Repair check on m (#89)

mice 3.0.0

Version 3.0 represents a major update that implements the following features:

1. blocks: The main algorithm iterates over blocks. A block is simply a collection of variables. In the common MICE algorithm each block was equivalent to one variable, which - of course - is the default; The blocks argument allows mixing univariate imputation method multivariate imputation methods. The blocks feature bridges two seemingly disparate approaches, joint modeling and fully conditional specification, into one framework;

2. where: The where argument is a logical matrix of the same size of data that specifies which cells should be imputed. This opens up some new analytic possibilities;

3. Multivariate tests: There are new functions D1(), D2(), D3() and anova() that perform multivariate parameter tests on the repeated analysis from on multiply-imputed data;

4. formulas: The old form argument has been redesign and is now renamed to formulas. This provides an alternative way to specify imputation models that exploits the full power of R’s native formula’s.

5. Better integration with the tidyverse framework, especially for packages dplyr, tibble and broom;

6. Improved numerical algorithms for low-level imputation function. Better handling of duplicate variables.

7. Last but not least: A brand new edition AND online version of Flexible Imputation of Missing Data. Second Edition.

mice 2.46.9 (2017-12-08)

• simplify code for mids object in mice (thanks stephematician) (#61)
• simplify code in rbind.mids (thanks stephematician) (#59)
• repair bug in pool.compare() in handling factors (#60)
• fixed bug in rbind.mids in handling where (#59)
• add new arguments to as.mids(), add as()
• update contact info
• resolved problem cart not accepting a matrix (thanks Joerg Drechsler)
• Adds generalized pool() to list of models
• Switch to 3-digit versioning

mice 2.46 (2017-10-22)

• Allow for capitals in imputation methods

mice 2.45 (2017-10-21)

• Reorganized vignettes to land on GitHUB pages

mice 2.44 (2017-10-18)

• Code changes for robustness, style and efficiency (Bernie Gray)

mice 2.43 (2017-07-20)

• Updates the ampute function and vignettes (Rianne Schouten)

mice 2.42 (2017-07-11)

• Rename mice.impute.2l.sys to mice.impute.2l.lmer

mice 2.41 (2017-07-10)

• Add new feature: whereargument to mice
• Add new wy argument to imputation functions
• Add mice.impute.2l.sys(), author Shahab Jolani
• Update with many simplifications and code enhancements
• Fixed broken cbind() function
• Fixed Bug that made the pad element disappear from mids object

mice 2.40 (2017-07-07)

• Fixed integration with lattice package
• Updates colors in xyplot.mads
• Add support for factors in mice.impute.2lonly.pmm()
• Create more robust version of as.mids()
• Update of ampute() by Rianne Schouten
• Fix timestamp problem by rebuilding vignette using R 3.4.0.

mice 2.34 (2017-04-24)

• Update to roxygen 6.0.1
• Stylistic changes to mice function (thanks Ben Ogorek)
• Calls to cbind.mids() replaced by calls to cbind()

mice 2.31 (2017-02-23)

• Add link to miceVignettes on github (thanks Gerko Vink)
• Add package documentation
• Add README for GitHub
• Add new ampute functions and vignette (thanks Rianne Schouten)
• Rename ccn –> ncc, icn –> nic
• Change helpers cc(), ncc(), cci(), ic(), nic() and ici() use S3 dispatch
• Change issues tracker on Github - add BugReports URL #21
• Fixed multinom MaxNWts type fix in polyreg and polr #9
• Fix checking of nested models in pool.compare #12
• Fix as.mids if names not same as all columns #11
• Fix extension for glmer models #5

mice 2.29 (2016-10-05)

• Add midastouch: predictive mean matching for small samples (thanks Philip Gaffert, Florian Meinfelder)

mice 2.28 (2016-10-05)

• Repaired dots problem in rpart call

mice 2.27 (2016-07-27)

• Add ridge to 2l.norm()
• Remove .o files

mice 2.25 (2015-11-09)

• Fix as.mids() bug that crashed miceadds::mice.1chain()

mice 2.23 (2015-11-04)

• Update of example code on /doc

• Remove lots of dependencies, general cleanup

• Fix impute.polyreg() bug that bombed if there were no predictors (thanks Jan Graffelman)

• Fix as.mids() bug that gave incorrect \(m\) (several users)

• Fix pool.compare() error for lmer object (thanks Claudio Bustos)

• Fix error in mice.impute.2l.norm() if just one NA (thanks Jeroen Hoogland)

mice 2.22 (2014-06-11)

• Add about six times faster predictive mean matching
• pool.scalar() now can do Barnard-Rubin adjustment
• pool() now handles class lmerMod from the lme4 package
• Added automatic bounds on donors in .pmm.match() for safety
• Added donors argument to mice.impute.pmm() for increased visibility
• Changes default number of trees in mice.impute.rf() from 100 to 10 (thanks Anoop Shah)
• long2mids() deprecated. Use as.mids() instead
• Put lattice back into DEPENDS to find generic xyplot() and friends
• Fix error in 2lonly.pmm (thanks Alexander Robitzsch, Gerko Vink, Judith Godin)
• Fix number of imputations in as.mids() (thanks Tommy Nyberg, Gerko Vink)
• Fix colors to mdc() in example mice.impute.quadratic()
• Fix error in mice.impute.rf() if just one NA (thanks Anoop Shah)
• Fix error in summary.mipo() when names(x$qbar) equals NULL (thanks Aiko Kuhn)
• Fix improper testing in ncol() in mice.impute.2lonly.mean()

mice 2.21 02-05-2014 SvB

• FIXED: compilation problem in match.cpp on solaris CC

mice 2.20 02-02-2014 SvB

• ADDED: experimental fastpmm() function using Rcpp
• FIXED: fixes to mice.impute.cart() and mice.impute.rf() (thanks Anoop Shah)

mice 2.19 21-01-2014 SvB

• ADDED: mice.impute.rf() for random forest imputation (thanks Lisa Doove)
• CHANGED: default number of donors in mice.impute.pmm() changed from 3 to 5. Use mice(…, donors = 3) to get the old behavior.
• CHANGED: speedup in .norm.draw() by using crossprod() (thanks Alexander Robitzsch)
• CHANGED: speedup in .imputation.level2() (thanks Alexander Robitzsch)
• FIXED: define MASS, nnet, lattice as imports instead of depends
• FIXED: proper handling of rare case in remove.lindep() that removed all predictors (thanks Jaap Brand)

mice 2.18 31-07-2013 SvB

• ADDED: as.mids() for converting long format in a mids object (thanks Gerko Vink)
• FIXED: mice.impute.logreg.boot() now properly exported (thanks Suresh Pujar)
• FIXED: two bugs in rbind.mids() (thanks Gerko Vink)

mice 2.17 10-05-2013 SvB

• ADDED: new form argument to mice() to specify imputation models using forms (contributed Ross Boylan)
• FIXED: with.mids(), is.mids(), is.mira() and is.mipo() exported
• FIXED: eliminated errors in the documentation of pool.scalar()
• FIXED: error in mice.impute.ri() (thanks Shahab Jolani)

mice 2.16 27-04-2013 SvB

• ADDED: random indicator imputation by mice.impute.ri() for nonignorable models (thanks Shahab Jolani)
• ADDED: workhorse functions .norm.draw() and .pmm.match() are exported
• FIXED: bug in 2.14 and 2.15 in mice.impute.pmm() that produced an error on factors
• FIXED: bug that crashed R when the class variable was incomplete (thanks Robert Long)
• FIXED: bug in 2l.pan and 2l.norm by convert a class factor to integer (thanks Robert Long)
• FIXED: warning eliminated caused by character variables (thanks Robert Long)

mice 2.15 - 02-04-2013 SvB

• CHANGED: complete reorganization of documentation and source files
• ADDED: source published on GitHub.com
• ADDED: new imputation method mice.impute.cart() (thanks Lisa Doove)
• FIXED: calculation of degrees of freedom in pool.compare() (thanks Lorenz Uhlmann)
• FIXED: error in DESCRIPTION file (thanks Kurt Hornik)

mice 2.14 - 11-03-2013 / SvB

• ADDED: mice.impute.2l.mean() for imputing class means at level 2
• ADDED: sampler(): new checks of degrees of freedom per variable at iteration 1
• ADDED: function check.df() to throw a warning about low degrees of freedom
• FIXED: tolower() added in “2l” test in sampler()
• FIXED: conversion of factors that have other roles (multilevel) in padModel()
• FIXED: family argument in call to glm() in glm.mids() (thanks Nicholas Horton)
• FIXED: .norm.draw(): evading NaN imputed values by setting df in rchisq() to a minimum of 1
• FIXED: bug in mice.df() that prevented the classic Rubin df calculation (thanks Jean-Batiste Pingaul)
• FIXED: bug fixed in mice.impute.2l.norm() (thanks Robert Long)
• CHANGED: faster .pmm.match2() from version 2.12 renamed to default .pmm.match()

mice 2.13 - 03-07-2012 / SvB

• ADDED: new multilevel functions 2l.pan(), 2lonly.norm(), 2lonly.pmm() (contributed by Alexander Robitzsch)
• ADDED: new quadratic imputation function: quadratic() (contributed by Gerko Vink)
• ADDED: pmm2(), five times faster than pmm()
• ADDED: new argument data.init in mice() for initialization (suggested by Alexander Robitzsch)
• ADDED: mice() now accepts pmm as method for (ordered) factors
• ADDED: warning and a note to 2l.norm() that advises to use type=2 for the predictors
• FIXED: bug that chrashed plot.mids() if there was only one incomplete variable (thanks Dennis Prangle)
• FIXED: bug in sample() in .pmm.match() when donor=1 (thanks Alexander Robitzsch)
• FIXED: bug in sample() in mice.impute.sample()
• FIXED: fixed ‘?data’ bug in check.method()
• REMOVED: wp.twin(). Now available from the AGD package

mice 2.12 - 25-03-2012 / SvB

• UPDATE: version for launch of Flexible Imputation of Missing Data (FIMD)
• ADDED: code fimd1.r-fim9.r to inst/doc for calculating solutions in FIMD
• FIXED: more robust version of supports.transparent() (thanks Brian Ripley)
• ADDED: auxiliary functions ifdo(), long2mids(), appendbreak(), extractBS(), wp.twin()
• ADDED: getfit() function
• ADDED: datasets: tbc, potthoffroy, selfreport, walking, fdd, fdgs, pattern1-pattern4, mammalsleep
• FIXED: as.mira() added to namespace
• ADDED: functions flux(), fluxplot() and fico() for missing data patterns
• ADDED: function nelsonaalen() for imputing survival data
• CHANGED: rm.whitespace() shortened
• FIXED: bug in pool() that crashed on nonstandard behavior of survreg() (thanks Erich Studerus)
• CHANGED: pool() streamlined, warnings about incompatibility in lengths of coef() and vcov()
• FIXED: mdc() bug that ignored transparent=FALSE argument, now made visible
• FIXED: bug in md.pattern() for >32 variables (thanks Sascha Vieweg, Joshua Wiley)

mice 2.11 - 21-11-2011 / SvB

• UPDATE: definite reference to JSS paper
• ADDED: rm.whitespace() to do string manipulation (thanks Gerko Vink)
• ADDED: function mids2mplus() to export data to Mplus (thanks Gerko Vink)
• CHANGED: plot.mids() changed into trellis version
• ADDED: code used in JSS-paper
• FIXED: bug in check.method() (thanks Gerko Vink)

mice 2.10 - 14-09-2011 / SvB

• FIXED: arguments dec and sep in mids2spss (thanks Nicole Haag)
• FIXED: bug in keyword “monotone” in mice() (thanks Alain D)

mice 2.9 - 31-08-2011 / SvB

• FIXED: appropriate trimming of ynames and xnames in Trellis plots
• FIXED: exported: spss2mids(), mice.impute.2L.norm()
• ADDED: mice.impute.norm.predict(), mice.impute.norm.boot(), mice.impute.logreg.boot()
• ADDED: supports.transparent() to detect whether .Device can do semi-transparent colors
• FIXED: stringr package is now properly loaded
• ADDED: trellis version of plot.mids()
• ADDED: automatic semi-transparancy detection in mdc()
• FIXED: documentation of mira class (thanks Sandro Tsang)

mice 2.8 - 24-03-2011 / SvB

• FIXED: bug fixed in find.collinear() that bombed when only one variable was left

mice 2.7 - 16-03-2011 / SvB

• CHANGED: check.data(), remove.lindep(): fully missing variables are imputed if allow.na=TRUE (Alexander Robitzsch)
• FIXED: bug in check.data(). Now checks collinearity in predictors only (Alexander Robitzsch)
• CHANGED: abbreviations of arguments eliminated to evade linux warnings

mice 2.6 - 03-03-2011 / SvB

• ADDED: bwplot(), stripplot(), densityplot() and xyplot() for creating Trellis graphs
• ADDED: function mdc() and mice.theme() for graphical parameters
• ADDED: argument passing from mice() to lower-level functions (requested by Juned Siddique)
• FIXED: erroneous rgamma() replaced by rchisq() in .norm.draw, lowers variance a bit for small n
• ADDED: with.mids() extended to handle expression objects
• FIXED: reporting bug in summary.mipo()
• CHANGED: df calculation in pool(), intervals may become slightly wider
• ADDED: internal functions mice.df() and df.residual()
• FIXED: error in rm calculation for “likelihood” in pool.compare()
• CHANGED: default ridge parameter changed

mice 2.5 - 06-01-2011 / SvB

• ADDED: various stability enhancements and code clean-up
• ADDED: find.collinear() function
• CHANGED: automatic removal of constant and collinear variables
• ADDED: ridge parameter in .norm.draw() and .norm.fix()
• ADDED: mice.impute.polr() for ordered factors
• FIXED: chainMean and chainVar in mice.mids()
• FIXED: iteration counter for mice.mids and sampler()
• ADDED: component ‘loggedEvents’ to mids-object for logging actions
• REMOVED: annoying warnings about removed predictors
• ADDED: updateLog() function
• CHANGED: smarter handling of model setup in mice()
• CHANGED: .pmm.match() now draws from the three closest donors
• ADDED: mids2spss() for shipping a mids-object to SPSS
• FIXED: change in summary.mipo() to work with as.mira()
• ADDED: function mice.impute.2L.norm.noint()
• ADDED: function as.mira()
• FIXED: global assign() removed from mice.impute.polyreg()
• FIXED: improved handling of factors by complete()
• FIXED: improved labeling of nhanes2 data

mice 2.4 - 17-10-2010 / SvB

• ADDED: pool() now supports class ‘polr’ (Jean-Baptiste Pingault)
• FIXED: solved problem in mice.impute.polyreg when one of the variables was named y or x
• FIXED: remove.lindep: intercept prediction bug
• ADDED: version() function
• ADDED: cc(), cci() and ccn() convenience functions

mice 2.3 - 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

mice 2.2 - 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)

mice 2.1 - 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

mice 2.0 - 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
• REMOVED: 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()
• REMOVED: 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

mice 1.21 - 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

mice 1.16 - 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.

mice 1.15 - 01/09/2006

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

mice 1.14R - 9/26/2005 11:44AM

• 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

mice 1.13

• Changed function checkImputationMethod, Feb 6, 2004

mice 1.12

• Maintainance, S-Plus 6.1 and R 1.8 unicode, January 2004

mice 1.1

• R version (with help of Peter Malewski and Frank Harrell), Feb 2001

mice 1.0

• Original S-PLUS release, June 14 2000