dear professor: thank you for your help,witn your help i develop the nomogram successfully. after that i want to do the internal validation to the model.i ues the bootpred to do it,and then i encounter problem again,just like that.(´íÎóÓÚerror to :complete.cases(x, y, wt) : ²»ÊÇËùÓеIJÎÊý¶¼Ò»Ñù³¤(the length of the augment was different)) i hope you tell me where is the mistake,and maybe i have chosen the wrong function. thank you turly yours ...... load package 'rms' > ddist <- datadist(dfr) > options(datadist='ddist') > n<-100 > set.seed(10) > T.Grade<-factor(0:3,labels=c("G0", "G1", "G2","G3")) > Sex<-factor(sample(0:1, 100, replace=TRUE),labels=c("F","M")) > Smoking<-factor(sample(0:1, 100, replace=TRUE),labels=c("No","yes")) > dfr$L<-with(dfr,0.559*as.numeric(T.Grade)-0.896*as.numeric(Smoking)+0.92*as.numeric(Sex)-1.338) > dfr$y <- with(dfr, ifelse(runif(n) < plogis(L), 1, 0) ) > dfr <- data.frame(T.Grade,Sex,Smoking, L, y) > ddist <- datadist(dfr) > options(datadist='ddist') > f<-lrm(y~T.Grade +Sex+Smoking, data=dfr) > nom<-nomogram(f,fun=function(x)1/(1+exp(-x)),fun.at=c(.01,.05,seq(.1,.9,by=.2),.9,1),funlabel="Risk > of Death") > plot(nom, xfrac=0.45) load package bootstrap .................the problem.................... > theta.fit <- function(dfr,y){lsfit(dfr,y)} > theta.predict <- function(fit,dfr){cbind(1,dfr)%*%fit$coef} > sq.err <- function(y,yhat) { (y-yhat)^2} > results <- bootpred(x,y,50,theta.fit,theta.predict,err.meas=sq.err) ´íÎóÓÚerror to :complete.cases(x, y, wt) : ²»ÊÇËùÓеIJÎÊý¶¼Ò»Ñù³¤(the length of the augment was different)
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