I am analyzing a dataset. There I have 4 variables that are used to diagnose a disease. Among them, 3 were "Lab test report findings" e.g. Test A, Test B, Test C and 1 "clinical findings" i.e. "Test D (which is obtained by the clinical examination of the patient and is not established for the confirmatory diagnosis of the disease).
To confirm the diagnosis of the disease e.g. "Dengue", Each of the 3 lab tests i.e. A, B, C can independently be used for the confirmatory diagnose of Dengue. In my research, patients had done at least one of the 3 tests to confirm the disease. Some might have done all the 3 tests.
Also, among the patients, a great proportion had shown the positive result of the "Test D".
I want to establish that, the "Test D" could be one of the confirmatory tests along with the other 3 tests i.e. A, B, C. On top of that, "Test D" could be more accurate and reliable to confirm the Dengue compared to other lab tests i.e. A, B, C.
So, what statistical test should I be used to prove and compare the effectiveness of this clinical examination findings? Also, suggest me some graphs, that can visualize with this case)
N.B. All 4 tests had a dichotomous answer. The findings of these tests can either be positive or negative.
Do you have the information on the true state of the patients (to be able to say which test results were false positive and false negative)?
Hello, Dr. Jochen Wilhelm
Unfortunately I do not have any information on true state of the patients.
Thanks
Hello.
For multiple comparaison, You can use freidman test in which you can add a graph for visualution of results. Good luck.
Then I don't understand how you would use the data to "confirm the diagnosis of the disease". You need a "gold standard", a "best way" to diganose the disease with high precision and accuracy. Otherwise it always remains unclear if the test results are correct or false (positive or negative). Since not all lab tests are performed on all patients, you can not even use the concordance among these tests.
Dr. Jochen Wilhelm Thanks for the suggestions. Actually, it was not planned while conducting the study. While analyzing, it came up to our mind, is something like this possible or not?
But what do you think about, Freidman Test mentioned by Aoautef Mahani?
It's not possible.
To Aoautef's response (since you asked): I think this is nonsense - at least not helpful. There is no sensible hypothesis you can test with Friedman's test (Freidman is a typo!) given your data. This also allpies to other procedures (e.g. ANOVA or whith whatever people may come up). There is no sensible hypothesis you can test. Sure: there are many hypotheses you can test - but these simply make no sense and they don't adress the question you are asking. You could adress your question only if you knew the true state of the patients or if you had a gold standard.
So you had an idea, now you found that it's impossible. Don't waste more time on that.
You should start all over again, recalibrating everything on the result you want to achieve.
Dear, Dr. Gioacchino de Candia
Thanks for your concern. We do not need to restart everything as this was not our objective to show the authenticity of "Test D". Simply a new research question was raised while we were analyzing our data. We have a large sample with several test results, so I just give it a try!
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