I am comparing three diagnostic tests in human. How could a ROC curve help me to determine which is the best and how I could make use of all the data I get when I use SPSS?
ROC curve is useful for comparing two or more diagnostic tests. It is more efficient way to display the relationship between sensitivity and specificity for tests that have continuous outcome, to conduct ROC using SPSS please see the following link
http://www.youtube.com/watch?v=WO8Re7YqnP0
I hope this help u
Adding to Mr. Mahfouz's answer, since you are trying to compare three diagnostic tests, you can estimate the area under curve (AUC) for each of the ROC curves, in order to compare between the tests.
I did this years ago, can't remember well, but as per the first answer re; sensitivity and specificity
Hi,
Thank you,sir for the advice and I did it before I reply and was helpful in the writing up .
Classification Assessment Methods
This paper introduces a detailed explanation with numerical examples many classification assessment methods or classification measures such as:
Accuracy, sensitivity, specificity, ROC curve, Precision-Recall curve, AUC score and many other metrics. In this paper, many details about the ROC curve, PR curve, and Detection Error Trade-off (DET) curve. Moreover, many details about some measures which are suitable for imbalanced data are explained.
Your comments are highly appreciated.
https://ac.els-cdn.com/S2210832718301546/1-s2.0-S2210832718301546-main.pdf?_tid=20353999-8c84-422a-8191-fd1059469272&acdnat=1536185805_03b19e159f0675a01f35512961973eb5
Presentation of the paper is here
https://www.researchgate.net/publication/327403649_Classification_assessment_methods_a_detailed_tutorial
Classification Assessment Methods
This paper introduces a detailed explanation with numerical examples many classification assessment methods or classification measures such as:
Accuracy, sensitivity, specificity, ROC curve, Precision-Recall curve, AUC score and many other metrics. In this paper, many details about the ROC curve, PR curve, and Detection Error Trade-off (DET) curve. Moreover, many details about some measures which are suitable for imbalanced data are explained.
Your comments are highly appreciated.
https://ac.els-cdn.com/S2210832718301546/1-s2.0-S2210832718301546-main.pdf?_tid=20353999-8c84-422a-8191-fd1059469272&acdnat=1536185805_03b19e159f0675a01f35512961973eb5
Presentation of the paper is here
https://www.researchgate.net/publication/327403649_Classification_assessment_methods_a_detailed_tutorial
- Badges
- Science topic
- Similar topics
- Mathematical Sciences
- Statistics
- Statistical Software
- SPSS