On Tue, 2006-10-31 at 11:17 -0600, Inman, Brant A. M.D. wrote: > I am looking for a book that discusses the theory of multiple imputation > (and other methods of dealing with missing data) and, just as > importantly, how to implement these methods in R or S-Plus. Ideally, > the book would have a structure similar to Faraway (Regression), > Pinheiro&Bates (Mixed Effects) and Wood (GAMs) and would be very modern > (i.e. published within the last couple of years). > > Any ideas? If such a book does not exist, one of the experts on this > help list should write it! (I will gladly buy the first copy.) > > Brant Inman > Mayo Clinic
One of the better references is: Statistical Analysis with Missing Data, Second Edition by Roderick J. A. Little, Donald B. Rubin Wiley-Interscience; 2nd edition (September 9, 2002) ISBN: 0471183865 http://www.amazon.com/Statistical-Analysis-Missing-Data-Second/dp/0471183865 In addition, see Frank Harrell's book "Regression Modeling Strategies", Chapter 3 on Missing Data. More information here: http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/RmS and see Frank's function 'aregImpute' in the Hmisc package. More information is here: http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/Hmisc with function specific help here: http://biostat.mc.vanderbilt.edu/s/Hmisc/html/aregImpute.html Within R, if you use: RSiteSearch("Missing Data") you will also get many hits. Finally, the Multivariate task view on CRAN has a Missing Data section about half way down the page: http://cran.r-project.org/src/contrib/Views/Multivariate.html HTH, Marc Schwartz ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
