Hi! Does anyone know how to do the test for goodness of fit of a logistic model (in rms package) after running fit.mult.impute?
I am using the rms and Hmisc packages to do a multiple imputation followed by a logistic regression model using lrm. Everything works fine until I try to run the test for goodness of fit: residuals(type=c("gof")) One needs to specify y=T and x=T in the fit. But I get a warning message when I do that with fit.multiple.impute. a<-aregImpute(~med.hist.err+ med.discr+newLiving+No.drugs+Days.categ+Los+Age+Ward+Sex, n.impute=20, nk=0,data=med.err) ddist<-datadist(Age,No.drugs,Days.categ, Sex, Living, Ward) options(datadist="ddist") fmi<-fit.mult.impute(med.hist.err~Age+No.drugs+Days.categ+Sex+Living+Ward, fitter=lrm, x=T, y=T,a,data=med.err) Error in 1:n.impute : NA/NaN argument In addition: Warning message: In 1:n.impute : numerical expression has 18 elements: only the first used It works to do the fit.mult.impute without x and y=T but then I get the following warning message when running residuals gof<-residuals(fmi, type=c("gof")) Error in residuals.lrm(fmi, type = c("gof")) : you did not specify y=T in the fit It was no problem to do the goodness of fit test when I ran the lrm on my complete data set without multiple imputation and fit.mult.impute. model.lrm<-lrm(med.hist.err~Age+No.drugs+Days +Sex+Living+Ward, x=TRUE, y=TRUE) gof<-residuals(model.lrm, type=c("gof")) Thanks Lina _________________ PhD student Linnaeus University Sweden [[alternative HTML version deleted]] ______________________________________________ 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.