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 <[EMAIL PROTECTED]> 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 > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help
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
______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
----------------------------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario, Canada L8S 4M4 email: [EMAIL PROTECTED] phone: 905-525-9140x23604 web: www.socsci.mcmaster.ca/jfox
______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
