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 [[alternative HTML version deleted]]
there is a green book by joe shafer ( I forget the name but it's
probsably on amazon ). I also
Can't say it's in the same format as faraday's book but I think
it's
fairly popular for multiple
Imputation techniques etc.
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From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Inman, Brant A.
M.D.
Sent: Tuesday, October 31, 2006 12:18 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Missing data analysis in R
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
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Have a look at J.L Schafer: ANALYSIS OF INCOMPLETE MULTIVARIATE DATA (1997). R already has several packages that deal with missing data imputation, I believe. Search around (please excuse my laziness). Don't know if you can get exactly what you want (an R/S -centric text), though. Bert Gunter Nonclinical Statistics 7-7374 -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Inman, Brant A. M.D. Sent: Tuesday, October 31, 2006 9:18 AM To: r-help at stat.math.ethz.ch Subject: [R] Missing data analysis in R 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 [[alternative HTML version deleted]] ______________________________________________ R-help at stat.math.ethz.ch 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.
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 ClinicOne 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