[R-sig-ME] var(ranef(Random Effect)) not the same as the variance component
@|m@h@rme| @end|ng |rom gm@||@com
Tue Sep 8 03:22:01 CEST 2020
This might seem irrelevant to my previous question, but it is from the post
you linked in your previous answer. So, is it correct language to say:
By including Random-Effects (e.g., random intercepts) of some subjects, we
are **controlling/adjusting/holding constant** subjects's random variations
in that random-effect (e.g., variation in subjects' initial status)?
On Mon, Sep 7, 2020 at 7:53 PM Simon Harmel <sim.harmel using gmail.com> wrote:
> Much appreciated, Ben. I will study those resources to better understand
> the estimation process.
> Thanks again,
> On Mon, Sep 7, 2020 at 6:25 PM Ben Bolker <bbolker using gmail.com> wrote:
>> Yes, that's correct.
>> > the covariance matrix of the empirical Bayes estimates obtained from
>> ranef() is related to the covariance of this posterior distribution [of
>> conditional modes/BLUPs] whereas VarCorr() is giving the D matrix, which
>> is the covariance matrix of the prior distribution of the random
>> effects. These are not the same.
>> On 9/7/20 7:22 PM, Simon Harmel wrote:
>> > Hello All,
>> > A very basic question. Generally, `var(ranef(Random Effect))` may not
>> > necessarily be the same as the variance component reported for that
>> > Effect in the model output, correct?
>> > Thank you all,
>> > Simon
>> > [[alternative HTML version deleted]]
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