[R-sig-ME] Errors in GLMER

[Thierry Onkelinx]

Dear Michiel,

Does it run with the random slope for trial. If I understand the
design correctly, you have only one observation per trial and per ID.
In that case a random slope for trial as an (ordered) factor won't
work.

Consider using trial as a continuous variable and use some polynomials
to model it.

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
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

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2018-06-24 23:41 GMT+02:00 Michiel Kiggen <michiel.kiggen using gmail.com>:
> Dear Reader,
>
> I'm trying to run a GLMER model for the following data:
> *2x scaled continous predictor* (sum score of 2 questionairres)
> *1x predictor being 10 trials* on a ultimatum game of which each trial is 1
> out of 10 possible options. (offer of a split of $20: e.g. you 1 and 19
> me). Inserted this a non ordered factor (10-levels) with sum-to-zero coding
> (contrast.sum).
> *1x dependent binary variable *being the response to the 10 trials valued
> at accepted (1) or reject (2). Entered as a factor.
>
> After the following model without correlations terms (I ran this model
> after failing to converge on a model without optimizers and the all_fit of
> that) I get the following errors:
>
> glmer(AoR ~ Trials * (sPredictor1*sPredictor2) + (1 | ID )+  (0 + Trials
> |ID),family = binomial, data = data, control = glmerControl(optCtrl =
> list(maxfun = 1e+9, optimizer = "bobyqa")))
>
>
> *fixed-effect model matrix is rank deficient so dropping 10 columns /
> coefficients*
> *Warning messages:*
> *1: In (function (npt = min(n + 2L, 2L * n), rhobeg = NA, rhoend = NA,  :*
> *  unused control arguments ignored*
> *2: In (function (iprint = 0L, maxfun = 10000L, FtolAbs = 0.00001, FtolRel
> = 1e-15,  :*
> *  unused control arguments ignored*
> 3: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
>   unable to evaluate scaled gradient
> 4: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
>   Model failed to converge: degenerate  Hessian with 11 negative eigenvalues
>
> I'm afraid I might be doing something wrong in handeling the DV or
> 10-factor level IV, which in turn, is causing the 3 errors in bold. Does
> anyone have suggestions. Or can some one tell me what the source of these
> errors are?
>
> Much obliged in advance,
>
> Kindest regards,
>
> Michiel Kiggen
>
>         [[alternative HTML version deleted]]
>
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