Greetings,
I am working on a logistic regression model in R and I am struggling with the
code, as it is a relatively new program for me. In searching Google for
'logistic regression diagnostics' I came Elizabeth Brown's Lecture 14 from her
Winter 2004 Biostatistics 515 course
(http://courses.washington.edu/b515/l14.pdf) . I found most of the code to be
very helpful, but I am struggling with the lines on to calculate the observed
and expected values in the 10 groups created by the cut function. I get error
messages in trying to create the E and O matrices: R won't accept assignment
of "fi1c==j" and it won't calculate the sum.
I am wondering whether someone might be able to offer me some assistance...my
search of the archives was not fruitful.
Here is the code that I adapted from the lecture notes:
fit <- fitted(glm.lyme)
fitc <- cut(fit, br = c(0, quantile(fit, p = seq(.1, .9, .1)),1))
t<-table(fitc)
fitc <- cut(fit, br = c(0, quantile(fit, p = seq(.1, .9, .1)), 1), labels = F)
t<-table(fitc)
#Calculate observed and expected values in ea group
E <- matrix(0, nrow=10, ncol = 2)
O <- matrix(0, nrow=10, ncol=2)
for (j in 1:10) {
E[j, 2] = sum(fit[fitc==j])
E[j, 1] = sum((1- fit)[fitc==j])
O[j, 2] = sum(pcdata$lymdis[fitc==j])
O[j, 1] = sum((1-pcdata$lymdis)[fitc==j])
}
Here is the error message: Error in Summary.factor(..., na.rm = na.rm) :
sum not meaningful for factors
I understand what it means; I just can't figure out how to get around it or how
to get the output printed in table form. Thank you in advance for any
assistance.
Mary Sullivan
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