[R-sig-ME] Convergence Error: 0 Fixed Correlations and More

[Thierry Onkelinx]

Dear Chris,

The correct syntax is (1 + FactorC | item) not (1 + FactorC || item).
Use a single |. I find the item.1 strange in the output. This might be
due to the syntax error.

The item random effect variances are quit high. You might have a
problem of quasi-complete separation. (1 + FactorC | item) might be
too complex for your data. Does (1 | item) converge?

Best regards,

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium

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


2015-09-21 18:37 GMT+02:00 Chris Heffner <heffner op umd.edu>:
> Hi,
>
> I'm running a psychology experiment with a few fixed effects and random
> factors, but for some of the models that I'm comparing I get an output that
> looks something like this:
>
> Generalized linear mixed model fit by maximum likelihood (Laplace
> Approximation) ['glmerMod']
>  Family: binomial  ( logit )
> Formula: FW ~ FactorA + FactorB + FactorC + FactorA:FactorC +
> FactorB:FactorC +      (1 | participant) + (1 + FactorC || item)
>    Data: east.acc1.subset
> Control: glmerControl(optCtrl = list(maxfun = 30000))
>
>      AIC      BIC   logLik deviance df.resid
>   1001.5   1066.9   -487.7    975.5     1120
>
> Scaled residuals:
>     Min      1Q  Median      3Q     Max
> -3.8335 -0.3041  0.1416  0.3566  2.8851
>
> Random effects:
>  Groups      Name        Variance  Std.Dev.  Corr
>  item     FactorCB       5.454e+00 2.3352985
>              FactorCS       3.097e+00 1.7597629 -0.81
>  item.1   (Intercept) 5.437e+00 2.3316731
>  participant (Intercept) 2.595e-08 0.0001611
> Number of obs: 1133, groups:  item, 55; participant, 23
>
> (Intercept)            0.1928833  0.0006222   310.0   <2e-16 ***
> FactorAInitial        1.8077886  0.0006222  2905.5   <2e-16 ***
> FactorB150        -0.4506653  0.0006220  -724.5   <2e-16 ***
> FactorB200        -0.5485114  0.0006220  -881.9   <2e-16 ***
> FactorCS                 -0.3923921  0.0006221  -630.8   <2e-16 ***
> FactorAInitial:FactorCS -0.0889474  0.0006221  -143.0   <2e-16 ***
> FactorB150:FactorCS   0.1347207  0.0006221   216.6   <2e-16 ***
> FactorB200:FactorCS   0.0682518  0.0006221   109.7   <2e-16 ***
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Correlation of Fixed Effects:
>             (Intr) FAIn FB150 FB200 FCS FAI:FCS FB150:FCS
> FAIntl 0.000
> FB150 0.000  0.000
> FB200 0.000  0.000  0.000
> FCS       0.000  0.000  0.000  0.000
> FaInt:FCS 0.000  0.000  0.000  0.000  0.000
> FB150:FCS 0.000  0.000  0.000  0.000  0.000 0.000
> FB200:FCS 0.000  0.000  0.000  0.000  0.000 0.000  0.000
>
> convergence code: 0
> Model failed to converge with max|grad| = 0.113738 (tol = 0.001, component
> 1)
> Model is nearly unidentifiable: very large eigenvalue
>  - Rescale variables?
>
> I've tried look through my data, as my first thought was that data was
> somehow miscoded, but I can't see anything that would be the matter.  A
> more complicated version of the model had the same problem until I got rid
> of a single participant (who seemed otherwise entirely unexceptional).  The
> more complicated model now converges fine, but this simpler one now has
> these issues.  I have an almost identical dataset that I've been doing
> almost exactly the same models with that hasn't been giving me similar
> problems.
>
> Any thoughts?
>
> Thank you,
>
> Chris
>
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>
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