[R-sig-ME] Logistic modelling with guessing parameter

[ken knoblauch]

Peter Harrison <pharr011 at ...> writes:

> 
> Hello Ben and Ken,
> 
> Thanks very much for your useful responses!
> 
> Ben - thanks for your hint re non-finite values in PIRLS, I'll bear that 
in mind for the future. I added
> non-finite warning checks to the link functions etc. and nothing 
came up this time, unfortunately.
> 
> You're right, all of the groups show complete separation - I hadn't 
thought too carefully about this but
> realise now that it will be a problem. I think I might have to merge the
 musical tracks into larger groups,
> perhaps by metre, genre, etc.
> 
> Thanks a lot for the great graph, too!
> 
> Ken - thanks for the heads-up about using the link directly from 
the psyphy package, that definitely
> simplifies things! Sorry, the code I gave and you ran is 
an example that does work: responses ~ accuracy +
> (1|p_ID). The model I was having problems with 
was when I added the "audio_name" predictor, i.e.
> responses ~ accuracy + audio_name + (1|p_ID).

Something that you can try is the mafc.cauchit link 
that would impose a less steep slope because of
the heavy tails of the Cauchy. This might be less
sensitive to complete separation sort of like a
regularization of the psychometric function slope.
I have used this link to correct for the bias introduced
by lapses at the upper asymptote instead of introducing
a lapse parameter which is not obvious how to do
otherwise with glmer. 


> 
> Best wishes,
> Peter
> 
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