Timeline for What is the benefit of using permutation tests?
Current License: CC BY-SA 3.0
13 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Dec 10, 2014 at 4:03 | history | edited | Glen_b | edited tags | |
| Jul 11, 2013 at 2:34 | history | edited | Glen_b | CC BY-SA 3.0 | fixed title |
| Jul 10, 2013 at 12:31 | history | edited | Tim | CC BY-SA 3.0 | added 584 characters in body |
| Jul 10, 2013 at 7:04 | history | rollback | Tim | Rollback to Revision 3 | |
| Jul 10, 2013 at 6:51 | vote | accept | Tim | ||
| Jul 10, 2013 at 6:50 | answer | added | Glen_b | timeline score: 18 | |
| Jul 10, 2013 at 6:19 | history | edited | Tim | CC BY-SA 3.0 | added 42 characters in body |
| Jul 10, 2013 at 6:05 | history | edited | Tim | CC BY-SA 3.0 | added 42 characters in body |
| Jul 10, 2013 at 6:01 | comment | added | Tim | Why? Is there some reference for explaining that? | |
| Jul 10, 2013 at 4:45 | comment | added | Tim | Does "T is the p-value (for cases where large U indicates deviation from the null and small U is consistent with it)", mean that the p-value for test statistic $U$ and sample $X$ is $T(X)$? | |
| Jul 10, 2013 at 4:22 | comment | added | Tim | @Glen_b: Thanks! Should $T(X)$ be equal to the p-value based on $U(X)$, for any sample $X$? If I understand correctly, I found it on page 5 of this slides So the benefit of using permutation test is to compute the p-value of the original test statistic $U$ without knowing the distribution of $X$ under null? Therefore, the distribution of $T(X)$ can be not necessarily uniform? | |
| Jul 10, 2013 at 4:18 | history | edited | Tim | CC BY-SA 3.0 | added 96 characters in body |
| Jul 10, 2013 at 3:49 | history | asked | Tim | CC BY-SA 3.0 |