Dear list, Usually we use Hosmer-Lemeshow test to test the goodness of fit for logistic model, but if I use it to test for Cox model, how can I get the observed probability for each group? Suppose I calculated the 5-year predicted probability using Cox model, then I split the dataset into 10 group according to this predicted probability. We should compare the observed probability with predicted probability within each group,but how to calculate this observed probability, should I use Kaplan-Meier to estimate it? how should I modify the following program,thanks.
hosmerlem = function(y, yhat, g=10) { cutyhat = cut(yhat, breaks = quantile(yhat, probs=seq(0, 1, 1/g)), include.lowest=TRUE) obs = xtabs(cbind(1 - y, y) ~ cutyhat) expect = xtabs(cbind(1 - yhat, yhat) ~ cutyhat) chisq = sum((obs - expect)^2/expect) P = 1 - pchisq(chisq, g - 2) return(list(chisq=chisq,p.value=P)) } -- View this message in context: http://r.789695.n4.nabble.com/Hosmer-Lemeshow-test-for-Cox-model-tp4635482.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.