[R-lang] Re: False convergence in mixed logit model

[Laura Suttle]

Hi Roger,

Thanks for the other list suggestion, I'll cross post to there.

Every variable in my data set is categorical, so I can't do that fix. I've
tried playing around with the maxIter parameter before, but I'm not sure I
was doing it right. Do you have any suggestions for where I can read more
about how to interpret the verbose output? I found some things but they
weren't very helpful.

Thanks,
Laura


On Thu, Nov 29, 2012 at 1:34 AM, Levy, Roger <rlevy@ucsd.edu> wrote:

>  Hi Laura,
>
>  This is a question that might be better answered on R-sig-ME, but
> briefly: I would be cautious with a model that reports false convergence;
> in my experience with this warning (and I am by no means expert on it), it
> can indicate that the optimization routine that determines the best-fit
> model parameters got stuck at a parameter estimate that is not near a true
> optimum, perhaps due to numerical issues.  You might try standardizing any
> continuous predictor variables you and rerunning the lmer() call.  It would
> be helpful to set the msVerbose control parameter to TRUE to see what the
> optimizer is doing.  Also, upping the maxIter and/or maxFN control
> parameters *might* be helpful.
>
>  I do not think that this warning message alone would be justification to
> omit a random effect.
>
>  Best & hope that this helps,
>
>  Roger
>
>  On Nov 28, 2012, at 8:58 PM PST, Laura Suttle wrote:
>
> Hello all,
>
>  I hope this question hasn't been asked before, but the internet isn't
> being of much help to me.
>
>  I am trying to run a mixed logit regression predicting whether
> participants use a novel verb in a particular construction or not depending
> on how they were exposed to that novel verb. I dummy coded the three
> conditions of the experiment into two dummy variables and have added two
> random effects, one for the motion used for the verb, the other for the
> verb itself (since these were all counterbalanced).
>
>  I can get this model to run fine, the problem is when I try to add any
> kind of random effect for the subjects themselves. I then get this error
> message:
>
>  Warning message:
> In mer_finalize(ans) : false convergence (8)
>
>  And all of the effects I had of the exposure type go away.
>
>  I've been trying to look up what this means and how to deal with it, but
> there are no clear solutions or explanations that I can find, but plenty of
> warning of how I should be skeptical of any output from a model with this
> warning. One suggestion I did find was that the subjects variable may be
> overfitting my data and there might be something to this: when participants
> are exposed to the verb in a certain way, they tend to only use the
> construction I'm looking for, with no variance in their responses. That
> said, I'm not sure that's right and I'd love a second opinion on either how
> I can fix this or whether I can use this as justification to not include
> the subjects random effect.
>
>  Thanks in advance for any help you can give,
> Laura Suttle
>
>
>
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