Timeline for Report p-values from model fitting or glht?
Current License: CC BY-SA 4.0
6 events
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| Jun 8, 2018 at 9:20 | comment | added | vkehayas | @Cristiano No, the fixed-effects coefficients are the estimates of the marginal (average) effect. If you want to investigate the per subject influence, you need to look at the distribution of the residuals per subject and, depending on exactly what you want to answer, the BLUPs. | |
| Jun 8, 2018 at 9:12 | history | edited | vkehayas | CC BY-SA 4.0 |
fix small inaccuracy
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| Jun 7, 2018 at 21:21 | comment | added | Cristiano | This is one side of the coin. The flip side would be that since this is a repeated measure design, I want to know whether grf1 affects the outcome variable coherently across subjects. My understanding, from a non statistician, is that for this I should look at the significance of the test. Correct? If so, what would you conclude given my numbers? | |
| Jun 7, 2018 at 21:05 | comment | added | Aaron - mostly inactive | Practically, you should ignore both the p-value and the idea of statistical significance. Both estimate 3.0 +/- 1.4, for a (rounded) 95% confidence interval of 0.2 to 5.8. Is an average difference somewhere between 0.2 and 5.8 practically meaningful? | |
| Jun 7, 2018 at 20:56 | comment | added | Cristiano | Thanks! I understand the issue of rounding due to small sample size, and also that of the arbitrary threshold. In practical terms though, what would you conclude from this analysis, that grf1 is significant or that is not? | |
| Jun 7, 2018 at 20:07 | history | answered | vkehayas | CC BY-SA 4.0 |