[R-sig-ME] nested mixed effects logistic regression binomial glm) results differ by function.

[Ben Bolker]

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On 15-04-24 06:08 AM, Malcolm Fairbrother wrote:
> Dear Lize,
> 
> Does it make any difference if you try: glmer(CC ~ predictor + (1 |
> area / household), family = binomial) ?
> 
> I may be wrong, but I thought the parentheses were important here.
> 
> 
> Best wishes, Malcolm
> 

  Nice catch! It would be interesting to try to develop a test (if not
exact, at least a heuristic) that would flag these problems ...

> 
> 
> Date: Thu, 23 Apr 2015 18:16:26 +0200
>> From: Lize van der Merwe <lizestats at gmail.com> To:
>> <r-sig-mixed-models at r-project.org> Subject: [R-sig-ME] nested
>> mixed effects logistic regression binomial glm)    results differ
>> by function.
>> 
>> Please advise:
>> 
>> I have a dichotomous outcome on 2500 individuals. From 18
>> geographical areas, and many households nested within areas. I
>> need to assess the association between various predictors and my
>> outcome, adjusting for the correlation within households, as well
>> as within areas. The following R functions provide dramatically
>> different results.
>> 
>> glmer(CC~predictor+1|area/household,family=binomial)
>> 
>> and
>> 
>> glmmPQL(CC~predictor, random=~1|area/household),family=binomial)
>> 
>> Why? Which is correct?
>> 
>> Thanks in advance.  (I posted this on another site too.)
>> 
>> Lize
>> 
> 
> [[alternative HTML version deleted]]
> 
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> 

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