Hi Andra,
I have been doing some ROC analysis for a new diagnosis test. I used the
pROC package to assess thresholds and compare different diagnosis tests to a
"gold standard". In your case, let say the gold standard are the observed
values y0.
Here is an example:
y0 <- sample(0:1,50,replace=TRUE
It is not possible to have one cutoff point unless you have a very strange
utility function. Nor is there a need for a cutoff when using a probability
model.
It is not advisable to compare models based on ROC area as this loses power.
A likelihood-based approach is recommended.
Frank
Andra Isan
Hello All,
I have used logistic regression glm in R and I am evaluating two models both
learned with glm but with different predictors. model1 <- glm (Y ~ x4+ x5+ x6+
x7, data = dat, family = binomial(link=logit))model2 <- glm (Y~ x1 + x2 +x3 ,
data = dat, family = binomial(link=logit))
and I
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