[R-sig-ME] LMER vs MLwiN

[W Robert Long]

I wasn't aware that I had asked anyone to  "do all the work" for me ! !

I am a statistics graduate student but I do not know R very well, so, in 
case anyone can point me towards any resources that can help, I would be 
most humbly grateful.


On 17/02/2012 9:18 PM, Doran, Harold wrote:
> I think you need to consult a local statistician who can help you at this point. This list really cannot do all the work for you.
>
> ----- Original Message -----
> From: W Robert Long<longrob604 at gmail.com>
> To: Doran, Harold
> Cc: r-sig-mixed-models at r-project.org<r-sig-mixed-models at r-project.org>
> Sent: Fri Feb 17 16:11:35 2012
> Subject: Re: [R-sig-ME] LMER vs MLwiN
>
> Thanks. Can you point me to any resources that would explain how to do
> that ? On the one hand it's great to know that it's straightforward, and
> I'm keen to learn,  but on the other it is rather depressing as I
> haven't a clue how to do it ;)
>
> On 17/02/2012 9:05 PM, Doran, Harold wrote:
>> It is straight forward to write your own resampling method for your fitted model. May be worth the effort for you
>> ________________________________________
>> From: W Robert Long [longrob604 at gmail.com]
>> Sent: Friday, February 17, 2012 3:45 PM
>> To: Doran, Harold
>> Cc: r-sig-mixed-models at r-project.org
>> Subject: Re: [R-sig-ME] LMER vs MLwiN
>>
>> Thank you. I tried mcmcsamp but I received the error "Update not yet
>> written". A little searching revealed that mcmcsamp may not work with
>> non-gaussian models ?
>>
>> On 17/02/2012 7:58 PM, Doran, Harold wrote:
>>> Sorry, meant to also add that you can try this as
>>>
>>>> example(mcmcsamp)
>>>> densityplot(samp0)
>>>> qqmath(samp0)
>>>
>>> I think you can then extend this your data to see if the distributional assumptions hold
>>>
>>>> -----Original Message-----
>>>> From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-
>>>> bounces at r-project.org] On Behalf Of Doran, Harold
>>>> Sent: Friday, February 17, 2012 2:55 PM
>>>> To: W Robert Long; r-sig-mixed-models at r-project.org; Douglas Bates
>>>> Subject: Re: [R-sig-ME] LMER vs MLwiN
>>>>
>>>> Raudenbush and Bryk do discuss this in their book if you require a text. But,
>>>> it is quite easy to show. At one point, there was an example of how to do this
>>>> using mcmcsamp() in the lme4 package (I think). But, I don't see the lattice
>>>> plots in that help page now.
>>>>
>>>>> -----Original Message-----
>>>>> From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-
>>>>> bounces at r-project.org] On Behalf Of W Robert Long
>>>>> Sent: Friday, February 17, 2012 2:33 PM
>>>>> To: r-sig-mixed-models at r-project.org; Douglas Bates
>>>>> Subject: Re: [R-sig-ME] LMER vs MLwiN
>>>>>
>>>>>
>>>>> On 17/02/2012 4:37 PM, Douglas Bates wrote:
>>>>> <snip>
>>>>>>> The estimates look pretty close, but the standard errors for the REs are
>>>>>>> quite different - I seem to remember the sampling variance of REs has a
>>>>>>> skewed distribution, but I don't know if this has anything to do with it
>>>> ?
>>>>>>
>>>>>> Those are not standard errors in the glmer output.  They are simply
>>>>>> the variance estimates on the standard deviation scale (i.e. 0.15567 =
>>>>>> sqrt(0.024233)).  The reason that glmer does not provide a standard
>>>>>> error for an estimate of a variance component is because they don't
>>>>>> make sense in most cases.  The distribution of the estimator is highly
>>>>>> skewed.
>>>>>>
>>>>> <snip>
>>>>>
>>>>> Thank you for that. Could you provide a reference for this latter point
>>>>> ? I have a copy of the Pinheiro and Bates (2000) book available in our
>>>>> library, if it's in there ? Otherwise, a published paper would be also
>>>>> be fine.
>>>>>
>>>>> _______________________________________________
>>>>> R-sig-mixed-models at r-project.org mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>>
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