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))
}
--
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Hosmer-Lemeshow test for Cox model
2 messages · wong jane, Frank E Harrell Jr
Any method that requires binning is problematic. Instead, take a look at the calibrate function in the rms package. There is a new option for continuous calibration curves for survival models. Frank jane.wong wrote
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))
}
----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Hosmer-Lemeshow-test-for-Cox-model-tp4635482p4635492.html Sent from the R help mailing list archive at Nabble.com.