[R-sig-ME] Testing Significance of Random Effects
Ben Bolker
bbo|ker @end|ng |rom gm@||@com
Fri Mar 12 15:59:54 CET 2021
I wouldn't generally recommend removing random effects on the basis
of null-hypothesis significance testing ... but others on this list
might, e.g. Matuschek et al. https://arxiv.org/pdf/1511.01864.pdf
(section 2.4) suggest backward stepwise removal with an alpha-level of 0.2.
Also see
https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#testing-significance-of-random-effects
On 3/12/21 9:43 AM, Marco Zanin wrote:
> To whom it may concern,
>
> My name is Marco Zanin, I am a PhD candidate in Sport & Exercise Physiology at Leeds Beckett University (Leeds, UK) and I work as Sport Scientist at Bath Rugby (Bath, UK).
>
> I am relatively new to lme4, but I was wondering whether you might help me to find a way to test the significance of the random effects in a model, whether the random effects improve/reduce the fit of the model and are thus necessary or if they could be removed from the model.
>
> I look forward to hearing from you.
>
> Kind regards,
>
> Marco Zanin
>
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