Timeline for Why does centering variable A influence my p values of factor B in the linear mixed effects model?
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 16, 2020 at 12:45 | vote | accept | CST | ||
| Aug 30, 2020 at 12:03 | comment | added | CST | Oh, I see... Thank you! | |
| Aug 30, 2020 at 11:58 | comment | added | Robert Long | You're welcome. No, I mean the size of the estimate. For example suppose I fitted a model for the impact of an intervention on BMI for severly obese people. Suppose the estimate was -0.1 and statistically significant (say, p = 0.04). I would say this is not practically significant. Suppose the estimate was -10 but not statistically significant (say, p = 0.06). The 2nd study would be far more interesting despite not having a "statistically significant" finding. | |
| Aug 30, 2020 at 11:47 | comment | added | CST | Thank you very much! By practical significance, you mean confidence intervals? (statisticsbyjim.com/hypothesis-testing/…) and I would conclude that the study group had an effect on the concentration if the CI of the beta is not including zero? | |
| Aug 30, 2020 at 10:48 | history | answered | Robert Long | CC BY-SA 4.0 |