leo_wa wrote:
I know that there are two method to apply the Hosmer and Lemeshow’s. One of
them is calculated based on the fixed and pre-determined cut-off points of
the estimated probability of success. One of them is calculated based on
the percentiles of estimated probabilities.
Both of these methods have been made obsolete by methods that do not
require any arbitrary groupings of predicted probabilities. See the
residuals.lrm function in the Design package and the reference in its
help file, to the Hosmer paper.
Frank
In the previous post,i find that the Hosmer and Lemeshow’s test how to use
in R.
hosmerlem <-
function (y, yhat, g = 10)
{
cutyhat <- cut(x, breaks = quantile(yhat, probs = seq(0,
1, 1/g)), include.lowest = T)
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)
c("X^2" = chisq, Df = g - 2, "P(>Chi)" = P)
}
I want to know how can i use the another method which is not use the
probability of success. i want to know how can i revise above program to
achieve an objective.
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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