Hi I constructed a mixed-effects model from longitudinal repeated measurements of lab values in 22 patients seperated into two groups with the groups as fixed effect using lme. I thought about using the jackknife procedure, i. e., removing any one subject and calculating the fixed effect, to assess the stability of the fixed effect and thereby validate the model. I suppose this has been done in the following study:
http://content.nejm.org/cgi/content/full/357/19/1903 (this may be restricted access, sorry) Is such an approach feasible? Also in the article results are confirmed by comparing the mixed model with a fitted least-squares regression. I understand that this can be achieved with lmlist, but only for for models without an additional fixed effect!? Are there any other good approaches to validate a mixed-effects model that will be accepted in medical peer review? -- Armin Goralczyk, M.D. -- Universitätsmedizin Göttingen Abteilung Allgemein- und Viszeralchirurgie Rudolf-Koch-Str. 40 39099 Göttingen -- Dept. of General Surgery University of Göttingen Göttingen, Germany -- http://www.gwdg.de/~agoralc ______________________________________________ R-help@r-project.org 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.
