Timeline for How to interpret random effect coefficients in glmer
Current License: CC BY-SA 4.0
4 events
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| Sep 19, 2020 at 1:03 | comment | added | Ben Bolker | If I interpret this correctly, you're worried that you can't interpret "Très competitif" as reducing mortality. That's incorrect. (1) the estimate is negative, which means that it is estimated to reduce mortality on average, across groups. (2) the estimate is significant, which means we're fairly certain that the effect is really negative (and not just due to noise in this data set). (3) the estimate is small relative to the difference across groups, which means that if we took samples from different groups and compared them, it might obscure this difference. | |
| Sep 19, 2020 at 0:42 | comment | added | Seydou GORO |
Thanks @Ben Bolker for your explaination that gave me a general idea of how to interpret the random effect. So I could not state that category " Très.competitif " of HHI_cat decrease mortality vs category of reference?
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| Sep 19, 2020 at 0:22 | vote | accept | Seydou GORO | ||
| Sep 18, 2020 at 23:49 | history | answered | Ben Bolker | CC BY-SA 4.0 |