Timeline for Is this p-hacking?
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
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| Feb 3, 2022 at 20:54 | comment | added | Michael Lew | The point made by @SextusEmpiricus about exploratory or preliminary studies is very important (+1), and yet rarely mentioned in discussions about p-hacking. For your study I would say that the possibility of being misled by exaggerations of the 'significance filter' is equally important. Read about both here: link.springer.com/chapter/10.1007/164_2019_286 | |
| Feb 3, 2022 at 16:39 | history | edited | Sextus Empiricus | CC BY-SA 4.0 | added 6 characters in body |
| Feb 3, 2022 at 15:58 | comment | added | Sextus Empiricus | @gazm2k5 But, if you are gonna take into account all sorts of different controls, in order to test some hypothesis (the null effect that there is no pay gap), then you end up p-hacking. | |
| Feb 3, 2022 at 15:52 | vote | accept | gazm2k5 | ||
| Feb 3, 2022 at 15:51 | comment | added | gazm2k5 | I see, that makes sense. Now that I think about it, maybe I do technically have a hypothesis. Whilst I was mainly exploring the data, I was already aware there was a wage gap, but as I add in controls I wanted to see how much that wage gap shrinks, so was using t-tests to confirm for statistical significance. So I guess my hypothesis would be "the wage gap does/does not exist when taking into account controls such as seniority, age, job role" etc. I would expect to see the pay gap shrink when taking more controls into account. | |
| Feb 3, 2022 at 15:10 | history | edited | Sextus Empiricus | CC BY-SA 4.0 | added 20 characters in body |
| Feb 3, 2022 at 15:00 | history | answered | Sextus Empiricus | CC BY-SA 4.0 |