[R-sig-ME] Estimation of variance components in random- and mixed-effects models

[Ben Bolker]

   See also:

https://stats.stackexchange.com/questions/37647/what-is-the-minimum-recommended-number-of-groups-for-a-random-effects-factor

https://www.biorxiv.org/content/10.1101/2021.05.03.442487v2

  (I should these links, and the blog post link, to the GLMM FAQ ...)

On 6/28/21 1:17 PM, Thierry Onkelinx wrote:
> Another issue is that you have too few levels to fit "cohort" as a 
> random effect. I wrote a blogpost on this a few years ago: 
> https://www.muscardinus.be/2018/09/number-random-effect-levels/ 
> <https://www.muscardinus.be/2018/09/number-random-effect-levels/>
> 
> Best regards,
> 
> ir. Thierry Onkelinx
> Statisticus / Statistician
> 
> Vlaamse Overheid / Government of Flanders
> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE 
> AND FOREST
> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
> thierry.onkelinx using inbo.be <mailto:thierry.onkelinx using inbo.be>
> Havenlaan 88 bus 73, 1000 Brussel
> www.inbo.be <http://www.inbo.be>
> 
> ///////////////////////////////////////////////////////////////////////////////////////////
> To call in the statistician after the experiment is done may be no more 
> than asking him to perform a post-mortem examination: he may be able to 
> say what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does not 
> ensure that a reasonable answer can be extracted from a given body of 
> data. ~ John Tukey
> ///////////////////////////////////////////////////////////////////////////////////////////
> 
> <https://www.inbo.be>
> 
> 
> Op ma 28 jun. 2021 om 16:31 schreef Ben Bolker <bbolker using gmail.com 
> <mailto:bbolker using gmail.com>>:
> 
>         Are you using lme4? (I'm 99% sure you are, but it's good to be
>     explicit.)
> 
>         Are all of your fixed predictors numeric (rather than
>     factor/categorical) ?
> 
>         Note that a convergence warning is a *warning*, not an error: have
>     you checked the troubleshooting steps in ?lme4::convergence (in
>     particular, scaling and centering your predictor variables might
>     help ...)
> 
>         cheers
>          Ben Bolker
> 
> 
>     On 6/28/21 10:17 AM, Amy Huang wrote:
>      > Dear all,
>      >
>      > I am examining maternal effects, and my data have three hierarchy
>     levels:
>      > clutches of the same female, females, and cohorts. My explanatory
>     variables
>      > are at the female level (female length, age) and at the cohort level
>      > (temperature).
>      >
>      > I would like to estimate the variance components of each
>     hierarchy level
>      > (i.e. relative amount of variance at each level) and then to find
>     out which
>      > factors (female length, age, temperature) explain most of the
>     variance. For
>      > these, I have two models:
>      >      offspring trait ~ 1 + (1 | cohort/female/clutch)
>      >      offspring trait ~ temperature + female length + age + (1 |
>      > cohort/female/clutch)
>      >
>      > The major problem is that I only have 3 cohorts (and so 3
>     temperatures).
>      >  From the first model I am able to get the information, but from
>     the second
>      > one there is an error message: "Model failed to converge with 1
>     negative
>      > eigenvalue: -2.0e+01". The error pops up probably because I have both
>      > temperature (fixed) and cohort (random) included. Is my approach
>     correct?
>      > And is there a way to fix this error?
>      >
>      > Thank you so much for your time.
>      >
>      > Best regards,
>      > Amy Huang
>      >
>      >       [[alternative HTML version deleted]]
>      >
>      > _______________________________________________
>      > R-sig-mixed-models using r-project.org
>     <mailto:R-sig-mixed-models using r-project.org> mailing list
>      > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>     <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models>
>      >
> 
>     _______________________________________________
>     R-sig-mixed-models using r-project.org
>     <mailto:R-sig-mixed-models using r-project.org> mailing list
>     https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>     <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models>
>