Agree with what Steve said.  It's quite possible that accounting for the
random effects is giving you results that are correct but initially
surprising. See for example this thread:
http://article.gmane.org/gmane.comp.lang.r.lme4.devel/11951

  [taking the liberty of cc'ing to r-sig-mixed-models]


On Thu, Jul 3, 2014 at 11:14 AM, Steve Walker <steve.walker@utoronto.ca>
wrote:

> Hi David,
>
> I explored this issue with the build-in cbpp example in lme4 (attached)
> but didn't find any problems.  We would need a reproducible example to
> pursue this any farther.
>
> Cheers,
> Steve
>
>
> On 2014-07-03, 2:44 AM, David Federer wrote:
>
>> Hi Ben,
>>
>> I need to run a multilevel logistic regression on a dataset that embeds a
>> nested structure.  I used the 'glmer' function to run a multilevel logit,
>> setting the 'family' parameter to 'binomial("logit")'. I expected the
>> function to regress the natural logarithm of the odds ratio ( ln(p/1-p)
>> )against the independent variable that I had specified. Instead, it
>> returned the natural logarithm of the proportion ( ln(p) ). Here is a
>> numerical example (for the intercept only model):
>>
>> In my dataset, p equals 0.2829. ln(p/p-1) should lie in the vicinity of
>> -0.9301. Instead glmer returned -1.2589 which approximates ln(0.2829)
>>
>> Is this an error in the 'glmer' function?
>>
>>
>> Kind Regards,
>>
>>
>>
>> David
>>
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>>
>>
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