[R-sig-ME] Very small random effect estimation in lmer but not in stata xtmixed

[Ben Bolker]

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On 12-05-04 09:46 AM, Joerg Luedicke wrote:
> Ben,
> 
> OP initially posted his problem over at the R-help forum:
> 
> https://stat.ethz.ch/pipermail/r-help/2012-May/311685.html
> 
> and so there was some discussion already.
> 
> Mohammed sent me his data off-list and there does not seem to be a 
> problem with his data, as far as I can see. The problem rather
> seems to be that lmer has some difficulties with estimating the
> variance parameter for varying intercepts when the sample size is
> small and the lower level variance is high relative to the group
> level variance. Please see my following post from the R-help
> forum:
> 
> https://stat.ethz.ch/pipermail/r-help/2012-May/311766.html
> 
> Any thoughts on this?
> 
> Joerg
> 

  I would love to see the data and/or the comparison with (1) nlme and
(2) the development version of lme4, to know if the problem is
fixed/fixable. My (not very informed at this point) guess is that it
is basically a nonlinear optimization problem.  I would like to see
the plot of REML vs. estimated RE variance -- my guess is that it has
two maxima ...

  (Thomas Lumley's answer on r-help looks wrong to me: I think he was
reading the model output too quickly and confused the correlation
among fixed effects with an among-RE correlation.)

  Ben Bolker


> On Fri, May 4, 2012 at 5:39 AM, Ben Bolker <bbolker at gmail.com>
> wrote:
>> Mohammed Mohammed <M.A.MOHAMMED at ...> writes:
>> 
>> 
>>> I am using the lmer function (in the lme4 library) to analyse
>>> some data where individuals are clustered into sets (using the
>>> SetID variable) with a single fixed effect (cc - 0 or 1). The
>>> lmer model and output is shown below.
>> 
>> 
>> 
>>> Whilst the fixed effects are consistent with stata (using
>>> xtmixed, see below), the std dev of the random effect for SetID
>>> is very very small (3.5803e-05)compared to stata's (see below
>>> 1.002). Any ideas why this should be happening please....?
>> 
>>> I am happy to share my data if that helps.
>>> 
>> 
>> Nothing really obvious pops out.  Have you tried nlme (i.e
>> library(nlme); lme(AnxietyScore ~cc, random=~1|SetID,data=mydf)) 
>> as a cross-check?
>> 
>> Can you send/post data?
>> 
>> Ben Bolker
>> 
>> _______________________________________________ 
>> R-sig-mixed-models at r-project.org mailing list 
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

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