Hi! I am trying to fit a Cox model with imputed data. However, the calibration function does not seem to work after applying fit.mult.impute. Secondly, which is the best method to validate the model?
This is the code... Could anyone help, please? aga_imp =aregImpute (~her2_cox+ecog_cox+bone_cox+nmet3_cox+ascitis_cox+Grade+nlr_cox,data =aga_NA, x=T, nk=0, n.impute =5) ddist=datadist(aga_sinNA) options(datadist="ddist") suv<- with(aga_NA, Surv(time,event)) cox <- fit.mult.impute(suv ~ her2_cox+ecog_cox+bone_cox+nmet3_cox+ascitis_cox+Grade+nlr_cox, cph, aga_imp, data=aga_NA, n.impute=5, pr=F, surv=T, time.inc=365 ) cal<-calibrate(cox, cmethod='KM', method='boot',u=365,B=10) Unfortunately I obtain this: Error in predab.resample(fit, method = method, fit = coxfit, measure = distance, : must have specified x=T and y=T on original fit -- View this message in context: http://r.789695.n4.nabble.com/Calibrate-after-fit-mult-impute-for-a-Cox-model-rms-package-tp4725353.html Sent from the datatable-help mailing list archive at Nabble.com. _______________________________________________ datatable-help mailing list [email protected] https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
