Today, there are many screening tests for a variety of diseases. Most of these tests are valid and reliable and for them calculated sensitivity, specificity, positive predictive value, negative predictive value and other diagnostic accuracy criteria. For now, I want to know How can compare the diagnostic accuracy of two or more screening test?
For example, we have three tests A, B, C and profile of each test is as follows (Profile of each test has been extracted from a separate article.):
Test A:
Sensitivity 87%, specificity 79%, positive predictive value 75%, and negative predictive value 64%
Test B:
Sensitivity 84%, specificity 81%, positive predictive value 70%, and negative predictive value 71%
Test c:
Sensitivity 90%, specificity 85%, positive predictive value 82%, and negative predictive value of 73%
Now I would like to compare the sensitivity, specificity, and other indicators statistically these tests together and determine whether are statistically significant differences between these tests or not?
Please suggest me related books and articles.
Please guide me. Thanks a lot
The authors are here on RG to this paper:
Article The diagnostic odds ratio: A single indicator of test performance
Since those are proportions you can compare them statistically using comparison tests for two proportions.
AUCs are also an important indicator about diagnostic accuracy.
Also for any comparison the nature of the disease and the test matters. So if the disease is HIV/AIDS you want to pick up as many as possible. If the next step after the test is an invasive procedure you would want the negative predictive you do not want to have too many false positives etc. In the end those considerations will often be more important than statistical testing. Other than that you can certainly test if the proportions are different easily for a simple test, but be aware that if these percentages are not sample based but population based any difference will be significant statistically no matter how small the difference is.
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