Provides a confusion matrix of classification statistics following logistic regression.
1  confusion_stat(pred=pred,obs=obs)

pred 
Predicted values 
obs 
Observed values 
The function has two arguments: predicted values, response values
confusion matrix
confusion_stat() must be loaded into memory in order to be effectve. As a function in LOGIT, it is immediately available to a user.
Rafael de Souza, ELTE University, and Joseph M. Hilbe, Arizona State University
Hilbe, Joseph M. (2015), Practical Guide to Logistic Regression, Chapman & Hall/CRC.
Hilbe, Joseph M. (2009), Logistic Regression Models, Chapman & Hall/CRC.
1 2 3 4 5 6 7 8 9 10 11 12  library(MASS)
library(LOGIT)
data(R84)
R84$cage < R84$age  mean(R84$age)
R84$cdoc < R84$docvis  mean(R84$docvis)
mylogit < glm(outwork ~ cdoc + female + kids + cage + factor(edlevel),
family=binomial, data=R84)
mu < predict(mylogit, type="response")
cutpoint<ROCtest(mylogit, fold=10, type="Sensitivity")$cut
mu[mu>=cutpoint]<1
mu[mu<cutpoint]<0
confusion_stat(mu, R84$outwork)

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