I recently concluded a clinical research which compared a certain parameter of one eye of a group of individuals to the the same parameter of the other eye of the same group of individuals. My statistical knowledge says these are unpaired (Independent) samples and as the parameter measured was a non - normally distributed continuous variable of 44 individuals, I used the Mann Whitney U test to compare the medians. I submitted the paper for publication and the reviewer came back with the following..
"The authors have performed the Mann Whitney U test while looking for differences between eyes. This is an example of paired data, between related samples, and calls for the non-parametric equivalent of the paired t-test, and thus the appropriate test ought to be the Wilcoxon test. But even here with 44 pairs, a paired t-test would be deemed a superior approach and would be quite appropriate, even if the sample data are non-normal, since with samples of this size the Central Limit Theorum kicks in, and justifies using statistical tests for parametric data. "
My question is ... Is it correct to call it Paired Sample? and Why?
Does it mean I have to re do my calculations?
Is it correct to say that for samples as small as these paired T test would be better?
"The authors have performed the Mann Whitney U test while looking for differences between eyes. This is an example of paired data, between related samples, and calls for the non-parametric equivalent of the paired t-test, and thus the appropriate test ought to be the Wilcoxon test. But even here with 44 pairs, a paired t-test would be deemed a superior approach and would be quite appropriate, even if the sample data are non-normal, since with samples of this size the Central Limit Theorum kicks in, and justifies using statistical tests for parametric data. "
My question is ... Is it correct to call it Paired Sample? and Why?
Does it mean I have to re do my calculations?
Is it correct to say that for samples as small as these paired T test would be better?