Multiple imputation
Dear Jonck, In addition, there are ports of both norm and mix in the contributed-packages section of CRAN. Regards, John
At 07:48 PM 6/12/2003 -0400, Frank E Harrell Jr wrote:
On Thu, 12 Jun 2003 23:57:45 +0200 Jonck van der Kogel <jonck at vanderkogel.net> wrote:
Hi all, I'm currently working with a dataset that has quite a few missing values and after some investigation I figured that multiple imputation is probably the best solution to handle the missing data in my case. I found several references to functions in S-Plus that perform multiple imputation (NORM, CAT, MIX, PAN). Does R have corresponding functions? I searched the archives but was not able to find anything conclusive there. Any help on this subject is much appreciated. Thanks, Jonck
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Look at the aregImpute function in the Hmisc package (http://hesweb1.med.virginia.edu/biostat/s/Hmisc.html). aregImpute uses the bootstrap, predictive mean matching, and flexible additive regression models to do multiple imputation. In one simulation study it performs as well as MICE but it runs much faster and does not assume linearity in the imputation models. I hope that someday we'll have simulation studies comparing aregImpute with NORM. --- Frank E Harrell Jr Prof. of Biostatistics & Statistics Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
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----------------------------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario, Canada L8S 4M4 email: jfox at mcmaster.ca phone: 905-525-9140x23604 web: www.socsci.mcmaster.ca/jfox