Timeline for Isn't it problematic to look at the data to decide to use a parametric vs. non-parametric test?
Current License: CC BY-SA 4.0
20 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 27 at 11:51 | answer | added | Frank Harrell | timeline score: 6 | |
| Jun 27 at 11:31 | answer | added | Sextus Empiricus | timeline score: 4 | |
| Jun 27 at 0:30 | answer | added | Christian Hennig | timeline score: 6 | |
| Jun 26 at 22:43 | answer | added | Ben Bolker | timeline score: 8 | |
| Jun 26 at 10:51 | comment | added | Nick Cox | In practice, it needs massive reform of scientific publication to get people to be explicit and honest about all the decisions they made -- e.g. about missing values, outliers, nonlinearity, etc. etc. -- and I am not even convinced that would be ideal. It would lead to unreadable papers no-one wants to read. There are many studies with more or less the right conclusions for the wrong reasons (e.g. citing significance tests that are irrelevant or ornamental). Reproducibility is important, but having access to others' data and being able to carry your own analyses are the largest part of that. | |
| Jun 26 at 10:43 | comment | added | Nick Cox | Just to stir up an already complicated and contentious question: I too still see people agonising about these matters and want to urge that this supposed dilemma -- parametric or non-parametric tests -- is largely a throwback to the 1950s. Using transformed scales and/or generalized linear models and/or using confidence intervals rather than significance tests go a long way towards many better analyses (though not all). This is not to deny the importance of laying out a plan of analysis in advance which is by far best practice and strongly advisable for say clinical trials. | |
| Jun 26 at 6:57 | answer | added | Glen_b | timeline score: 10 | |
| Jun 26 at 5:17 | comment | added | Glen_b | Given Gelman's explanation I think his claim is fine. The terminology (accept the null) I don't agree with but this is more an issue of phrasing not of the practical consequences of failure to reject (where he's quite clear about his actions). | |
| Jun 25 at 23:56 | history | became hot network question | |||
| Jun 25 at 20:37 | vote | accept | Coris | ||
| Jun 25 at 16:56 | comment | added | jginestet | Just a note about the blog from Gelman, which you provide a link to. He defines Type 2 errors as: "A Type 2 error is committed if we accept the null hypothesis when it is false.". One can NEVER accept the null, only fail to disprove it. Then he piles it on with this sentence: "*I’ve never in my professional life made a Type I error or a Type II error. *". After that, anything else he may say should be dismissed prima facie. | |
| Jun 25 at 16:49 | comment | added | Stephan Kolassa | What I personally find more concerning is when people really want to use a parametric test to answer question X, then find that the prerequisites are not given, so they use a nonparametric alternative... which actually answers a different question Y: stats.stackexchange.com/a/624494/1352 | |
| Jun 25 at 16:38 | history | edited | Frans Rodenburg | CC BY-SA 4.0 |
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| Jun 25 at 16:26 | comment | added | Coris | kjetil: It was not suggested among the "similar questions" when I wrote my question, but that's definitely relevant, thank you! | |
| Jun 25 at 16:21 | comment | added | kjetil b halvorsen♦ | Also look at stats.stackexchange.com/questions/551264/… | |
| Jun 25 at 16:20 | answer | added | Frans Rodenburg | timeline score: 20 | |
| Jun 25 at 16:02 | answer | added | Stephan Kolassa | timeline score: 26 | |
| Jun 25 at 16:02 | comment | added | Frans Rodenburg | You may be interested in this related question. | |
| S Jun 25 at 15:55 | review | First questions | |||
| Jun 25 at 16:20 | |||||
| S Jun 25 at 15:55 | history | asked | Coris | CC BY-SA 4.0 |