[R-sig-ME] statistical significance of group level intercepts in glmer

[Ben Bolker]

Unfortunately, you *can't* test significance of conditional modes (the
values that ranef()) returns; this is the price you pay for treating
them as random variables. However, you *can* extract the 'conditional
variances' of the conditional modes (see p. 28 of the vignette that
comes with lme4).  You can visualize these conditional variances via
`lattice::dotplot(ranef(fitted_model,condVar=TRUE))`.  The development
version of lme4 (on Github) has an as.data.frame method that makes it
easier to extract these values ...


On Tue, May 30, 2017 at 12:16 AM, Maaz Gardezi <maaz.gardezi at gmail.com> wrote:
> Hello,
>
> I am using glmer to model a mixed effects logistic regression. The output
> below shows the random intercepts and slope (zcwcexp) for 22 groups. I was
> wondering if there is any way of finding whether these are statistically
> significant?
>
>> ranef(addRandomCrossLevelInteraction)
> $subject
>    (Intercept)      zcwcexp
> 1   0.08913319 -0.007245956
> 2  -0.06997405  0.009194926
> 3  -0.77408045  0.247743815
> 4   0.07087457  0.048671025
> 5   0.16529502 -0.025846944
> 6   0.21978190  0.020381977
> 7   0.22628857 -0.060421227
> 8   0.67790616 -0.183998656
> 9   0.25113625 -0.109811064
> 10 -0.14569194 -0.039863882
> 11  0.13872081 -0.074646309
> 12 -0.23401794  0.069596589
> 13  0.96193273 -0.195829039
> 14 -0.46834542  0.092182158
> 15 -0.59465656  0.158177344
> 16 -0.06963680 -0.019127508
> 17 -0.25015416  0.067321201
> 18  0.32001648 -0.100452172
> 19 -0.40396733  0.120731775
> 20  0.07413768 -0.061477287
> 21 -0.08520228  0.044519621
> 22 -0.09427640  0.002166830
>
> Thanks!
>
> Maaz
>
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