For not normally distributed data, I used Kruskal-Wallis test to investigate the statistical significance between different variables. I performed an exercise with three different intensities (different weights w1, w2, w3), then with one weight at three different speeds (s1, s2, s3). The readings were observed from 3 different points(p1, p2, p3).
I opted for statistical significance among p1, p2, p3 at (w1 and w2 and w3) and at (s1 and s2 and s3). then i opted statistical significance among w1, w2, w3 for p1 and p2 and p3. then i opted statistical significance among s1, s2, s3 for p1 and p2 and p3. So, there are 36 independent Kruskal-Wallis tests.
After that, Mann-Whitney test was performed for pairs (post hoc analysis).
I got comment on the test that, "the piecemeal statistical approach, consisting of a very large number of comparisons made between dependent variables during different conditions, without corrections for multiple testing, renders it probable that “significant” results may well be due to chance."
Can someone please suggest where I am wrong, and how and where to adjust the p value?
Saad Javed Thanks Sir for response.
The data was collected from 25 subjects and it seems enough (as literature revealed).
I am looking for statistical significance among variables using one parameter at a time (say RMS). I used RMS values of 25 subjects for p1, and want to see the statistical significance among s1, s2 and s3. Kruskal-Wallis test is recommended for such test.
But in my case, i have to do 35 other tests (not in parallel but one after other). The comment is piecemeal approach is not appropriate. I'm simply confused over this point.
You need information on multiple comparisons methods. See thr link:
https://www.google.com/search?client=firefox-b-1-d&q=multiple+comparisons+tests
Best, David Booth
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