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

Ben Bolker bbo|ker @end|ng |rom gm@||@com
Mon Jun 28 16:25:06 CEST 2021

   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 ...)

    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]]
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