exact wilcox test and Bonferroni correction
netrunner wrote:
Dear Michael, thank you very much for your help. I perfomed the wilcox.exact function on each of the 8 items for the two groups that I am analysing (that is, I performed 8 times the wilcox test). Here an example for the values (ratings from a questionnaire) of one of the 8 items: a1=5 9 10 10 10 10 10 10 10 10 b1=7 5 10 NaN 10 10 8 10 10 8 9 9 wilcox.exact(a1,b1, alternative="two.sided", mu=0, paired=FALSE, exact=TRUE, conf.level=0.95) I obtained: data: a1 and b1 W = 73.5, p-value = 0.1514 alternative hypothesis: true mu is not equal to 0 Then I adjusted p-values using p.adjust. For the example above the p-bonferroni value was 1. The threshold p-value is 0.00625 (that is 0.05/8) Finally, because p-bonferroni > 0.00625 can I conclude that for each item my samples are from the same distribution? I am a little bit confused....
Yes... First, you need to EITHER adjust the p-value OR the threshold, not both. So coompare the p-bonferroni to 0.05, or the 0.1514 to 0.00625. In both cases, not significant, of course. Secondly, you NEVER conclude from statistics that samples are from the same distribution, only that this is an acceptable hypothesis, not contradicted by data. Third, it you have 8 separate items comparing two groups, how would pairwise.wilcox.test have worked? That function is designed to compare more than two groups pairwise (A vs B, B vs C, A vs C, etc.) with respect to a single outcome measure.
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