# Fisher's exact test for results of Wilcoxon-Mann-Whitney

I have two groups of subjects (9 and 13 people). And data from two condition for this groups. In each condition for each subjects I have some measurements. But number of measurements are different for conditions (for second condition more then for first). First I use Wilcoxon-Mann-Whitney test for every subject to find subjects with significant difference between conditions. Second I use Fisher's Exact Test for understand is there significant difference in numbers of subjects with difference between condition for my two groups. Say, in first group 4 subjects show significant difference, and 3 in second. So my fisher's table is [[4,5],[3,10]]. Is this make any sense? and if so, Shall I use any correction for multiple comparisons?

• Perhaps adding some more details and context would make this question clearer. For example, do you have repeated measures on each subject? How many Mann-Whitney tests did you do? Oct 14, 2012 at 13:40
• Yes I have repeated measures on each subject. But in second condition there are more measurements for each subject than in the first. I do 1 Mann-Whitney test for each subject. So it 9 for first group and 13 for second. Oct 14, 2012 at 13:57
• Can you tell us more about your research design? Is the following example more or less what you are doing? You have two groups, say men and women. You have two types of data for the men, say height and weight. You have the same two types of data for the women. You want to know which are heavier, men or women. You also want to know which are taller, men or women. Or is your design something different? Oct 14, 2012 at 15:19
• First of all, thank you for your attention. In term of your example, yes I have two groups - man and women. But I have one type of data, say blood pressure. I measured blood pressure n times for each subject. Then, say, they did physical exercises. And after it I again measured blood pressure for each subject, but m times. So m>n. I want to know in what group - man or women - chance of significant increase of blood pressure is more. Oct 14, 2012 at 15:56