- Thread starter bozatron
- Start date

I am using the ROC curve to assess the sensitivity and specificity of three measures, and using a the presence/absence of a diagnosis as the dichotomous variable (i.e., yes/no the participant has a diagnosis).

Hope that's clear, thanks for your help!

It is strange that I cannot seem to find any information on whether there are any assumptions to conduct this test though!

I recommended the decision tree based on thinking you are trying to create a decision rule based on 3 variable at the same time, correct or not? Look up what it takes to do a power calculation related to ROC curve, that may help with possible assumption or components to keep in mind.

So do scatterplots or bar graphs have assumptions? Probably just the intuitive basics related to what type of data it can handle. I think when it comes to assumptions, they may come into play related to using the Whitney-Mann test or comparing models. But the ROC Curve itself is just a graph.

I would highly recommend the book "Analyzing Receiver Operating Characteristic Curves with SAS: by Gonen. It provides a gentle introduction to many ROC Curve concepts including bias, and applying curves to ordinal and survival data. Plus, I think the book is fairly cheap and Gonen seems to be a person who regularly publishes technical papers in this area.

Take home thoughts, its just a graph and theory and assumptions may come into play downstream when finding a cut-point or making hypotheses related to AUC.