On Sun, 14 Oct 2007, coldeyes.Rhelp wrote: > Hi there: > i got a problem to get the prediction from a model recently. for > example if i use a survival analysis to predict the risk. i use the code > like below: i found the the prediction is not equal to (coef * x + coef > * sex) , could someone help me with why this happened?
The intercept is not identifiable in a Cox model, and the code takes advantage of this to center the variables. The predicted values are the values you expected, minus the mean. For the example in ?predict.coxph R> fit<-coxph(Surv(time,status)~x,data=aml) R> predict(fit) 1 2 3 4 5 6 7 -0.4776692 -0.4776692 -0.4776692 -0.4776692 -0.4776692 -0.4776692 -0.4776692 8 9 10 11 12 13 14 -0.4776692 -0.4776692 -0.4776692 -0.4776692 0.4378634 0.4378634 0.4378634 15 16 17 18 19 20 21 0.4378634 0.4378634 0.4378634 0.4378634 0.4378634 0.4378634 0.4378634 22 23 0.4378634 0.4378634 R> sum(predict(fit)) [1] 7.21645e-16 R> a<-coef(fit)*(aml$x=="Nonmaintained") R> a-mean(a) [1] -0.4776692 -0.4776692 -0.4776692 -0.4776692 -0.4776692 -0.4776692 [7] -0.4776692 -0.4776692 -0.4776692 -0.4776692 -0.4776692 0.4378634 [13] 0.4378634 0.4378634 0.4378634 0.4378634 0.4378634 0.4378634 [19] 0.4378634 0.4378634 0.4378634 0.4378634 0.4378634 > and can someone > explain to me how this command "predict(f, type="terms")" works? is > every partial prediction equal to coef*x=predict(f,type="terms")[,1] and > coef*sex=predict(f,type="terms")[,2]? it looks like they did not match. > however > "predict(f)=predict(f,type="terms")[,1]+predict(f,type="terms")[,2]" The same thing happens here. Each column of predict(,type="terms") sums to zero. In this case it is the same behaviour as lm() and glm(). -thomas ______________________________________________ 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.