[R-sig-ME] var-covar matrix in ranef

[Hester Lingsma]

Dear Prof Bates,
Thank you very much for this answer. I mean by the posterior estimates 
what you here refer to as the conditional means. So I was looking for 
the sd of the conditional means of the intecepts and the slopes. I 
already thought this was the square roots of the diagonal of the 2 by 2 
matrices, which is now confirmed. So thanks again!
Hester Lingsma

on 09-02-2010 16:13 Douglas Bates said the following:
> On Tue, Feb 9, 2010 at 2:50 AM, Hester Lingsma <h.lingsma at erasmusmc.nl> wrote:
>   
>> Dear R users,
>> If I fit a model with a random slope and a random intercept, the var-covar
>> matrix derived from PostVar from the function ranef is a 2 by 2 matrix for
>> each upper level subject. I want to use the posterior estimates (from ranef)
>> and their standard error from both the slope and the intercepct for each
>> upper level subject. Which elemants of the 2 by 2 matrixes to use for the se
>> of the posterior estimate?
>>     
>
> I'm not sure what "the posterior estimates" means but that term is
> probably my fault because the argument name is "postVar" for
> "posterior variance".  (Actually I think it is Harold Doran's fault
> because he is the one who suggested the term "posterior variance",
> which I not realize is a misnomer.)  Even though the argument name is
> "postVar", and I would prefer not to change it at this point, I now
> refer to the values returned by ranef as the conditional means (for
> linear mixed models, in more general models they are the conditional
> modes) of the random effects given the observed data and evaluated at
> the parameter estimates.  The conditional standard deviations of the
> random effects will be the square roots of the diagonal elements of
> the 2 by 2 matrices returned in the postVar attribute.
>   

-- 
_________________________________________________
Hester F. Lingsma, MSc
Dept of Public Health
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Erasmus MC
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