Obtain Youden Index from the 2-variable logistic regression model?

Dear all,

I am building a 2-variable predictive model and would like to obtain the best predicting point (i.e. Youden Index).

The most ideal predictive probability in my 2-variable model (based on the best balance between sensitivity & specificity in the AUC graph) is 0.335 (pls see the image attached).

My question is: How can I convert this probability back to the Youden Index (i.e. How can I conclude what age or BMI value will have the most utility in predicting the disease)?

Below is my code:

fit<- glm(disease~ Age + BMI, data=mydata, family=binomial)

pred.val.3 <- predict(fit, type ="response")
auc((mydata$disease), pred.val.3, plot=TRUE, print.thres="best", auc.polygon=TRUE, auc.polygon.col="lightblue", asp=FALSE,
print.auc=TRUE, print.auc.cex=2)
ci.auc((mydata$disease), pred.val.3)
1 Like

Oh that great, will be glad to knw that

Hi, do you know how to solve this problem? Any advice would be much appreciated.

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