[R-lang] False convergence in mixed logit model

[Laura Suttle]

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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