Timeline for Normality test before testing the difference between two groups. Is it necessary?
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
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| Nov 22, 2016 at 23:19 | comment | added | Michael Lew | Your results are at the margin for an asterisk by the arbitrary weak convention of taking less than 0.05 as sufficient. It's your responsibility to make the inference, not that of the statistical procedures. (The Mann-Witney U-test is probably a good choice.) | |
| Nov 22, 2016 at 23:16 | comment | added | Michael Lew | "I want to prove" Sorry, you can't. "Statistically those differences are real" Sorry, a meaningless phrase. What you are probably after is a statistical justification for making a claim or inference. Your results seem to support prior assertions, and so gain some mutual corroboration from that. | |
| Nov 22, 2016 at 23:11 | comment | added | juanmeque | Other studies claim that lesions under 20 have little risk of cancer and lesions greater than 20 are at increased risk of cancer, so my results are consistent with these studies. The difference in means is not very big but it can be relevant. I want to prove that statistically those differences are real and for that the test that shows me statistical significance (p <0.05) is U of Mann Whitney, so I wanted to know is correct to use this test in the study. | |
| Nov 22, 2016 at 22:53 | comment | added | Michael Lew | Oh, sorry, I misread the values. 0.07 and 0.0015 are a little more different than 0.007 and 0.015, but not that much. The result either way is not, of itself, particularly convincing of an effect or of the absence of an effect. You need to make inference on the basis of both the statistical result and reasoned scientific argument. Do you know more about the system than just your data? Is a distinction between 23 and 17 of great clinical significance? Was there any reason to suppose the values should be identical? Can you find another set of data? | |
| Nov 22, 2016 at 22:42 | comment | added | juanmeque | The mean in the cancer group is 23 and the mean in the free cancer group is 17. My doubt is that using statistical t-test the differences are not significant and using statistical mann Whitney the differences are significant | |
| Nov 22, 2016 at 22:29 | comment | added | Michael Lew | You want to make an inference about the lesion sizes, so you should look at the lesion sizes first, not the P-values from various tests. However, the tests agree quite well as the difference between P=0.007 and P=0.015 is trivial for almost all purposes. (And note that neither P-value is small enough to imply that the evidence for a difference between the groups is very strong.) | |
| Nov 22, 2016 at 21:44 | vote | accept | juanmeque | ||
| Nov 22, 2016 at 21:31 | comment | added | juanmeque | Excellent answer. Thank you! My study is retrospective observational. I have a sample with 17 women with cancer and 70 women without cancer. I want to know if the average lesion size are different in both groups. Test Kolmogorov-Smirnov Cancer group p = 0.200 Non-cancer group p = 0.000 T-test p = 0.07 Mann-Whitney U p = 0.015 Is it correct in this case to use a non-parametric test like U Mann-Whitney? | |
| Nov 22, 2016 at 20:44 | history | answered | Michael Lew | CC BY-SA 3.0 |