Dear R-Users,
The following question is more of general nature than a merely technical one. Nevertheless I hope someone get me some answers. I have been using the mice package to perform the multiple imputations. So far, everything works fine with the standard regressions analysis. However, I am wondering, if it is theoretically correct to perform nonparametric models (GAM, spline smoothing etc.) with multiple imputed datasets. If yes, how can I combine the results in order to show the uncertainty? In the research field of real estate economics, the problem of missing data is often ignored respectively unmentioned. However, GAM, spline smoothing etc. become increasingly popular. In my research, I would like to use multiple imputed datasets and GAM, but I am unsure how present single results. Again I want to apologize that this is a rather theoretical statistical question than a technical question on R. Thanks in advance for any hints and advices. Simon Simon P. Kempf Dipl.-Kfm. MScRE Immobilienökonom (ebs) Wissenschaftlicher Assistent Büro: IREBS Immobilienakademie c/o ebs Immobilienakademie GmbH Berliner Str. 26a 13507 Berlin Privat: Dunckerstraße 60 10439 Berlin Mobil: 0176 7002 6687 Email: <mailto:[EMAIL PROTECTED]> [EMAIL PROTECTED] [[alternative HTML version deleted]]
______________________________________________ R-help@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.
