[R-sig-ME] A question about multilevel models using the lmer package in R
Ben Bolker
bbo|ker @end|ng |rom gm@||@com
Tue Sep 13 16:56:35 CEST 2022
(This came through twice, for what it's worth.)
I can't immediately explain the phenomenon you observed (variance at
an upper level increasing when a covariate is added), but I'm not
shocked -- when there are multiple levels of variation, variation can
shift among them in surprising ways.
Can you clarify/expand on what you mean by "[evaluating] the impact
of a predictor on student/school-level intercepts"?
On 2022-09-13 10:46 a.m., Verena Hinze wrote:
> Dear mailing list at R-sig-mixed-models,
>
> I am very interested in using multilevel growth analyses for my research.
> I have come across a lot of very helpful tutorials on the internet, recommending the lmer package.
> However, I have one question for which I didn't manage to find the answer yet, and I was wondering whether you might be able to point me in the right direction...
>
> Specifically, I am interested in modelling three-level data (students nested within schools and within time). I am hoping to predict student outcomes by student-level and school-level predictors, and I have been using the lmer package in R to model the data.
>
> However, in the model output, I have noticed that sometimes the variance (for the student- or school-level intercepts or slopes) increases instead of decreases, compared to the simpler model without the respective predictor. This is contrary to what we would expect from ordinary regression analyses, where we expect the variance to decrease, if we add predictors to the model that help us to explain such variance.
>
> I was wondering what might be going on here? Have you encountered something similar before? And how could we evaluate the impact of a predictor on these student-/school-level intercepts and slopes in multi-level models instead?
>
> Any advice would be highly appreciated.
>
> With many thanks and kind regards,
>
> Verena
>
> Verena Hinze
> Postdoctoral Research Fellow
> Oxford Precision Psychiatry Lab
> University of Oxford, Department of Psychiatry
> Warneford Lane, Oxford, OX3 7JX
> E: verena.hinze using psych.ox.ac.uk
>
> [[alternative HTML version deleted]]
>
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--
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
(Acting) Graduate chair, Mathematics & Statistics
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