[R-sig-ME] var(ranef(Random Effect)) not the same as the variance component
Simon Harmel
@|m@h@rme| @end|ng |rom gm@||@com
Tue Sep 8 03:22:01 CEST 2020
Ben,
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,
> Simon
>
> On Mon, Sep 7, 2020 at 6:25 PM Ben Bolker <bbolker using gmail.com> wrote:
>
>> Yes, that's correct.
>>
>> From
>>
>> https://stats.stackexchange.com/questions/392283/interpreting-blups-or-varcorr-estimates-in-mixed-models/392307#392307
>>
>> > 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
>> Random
>> > Effect in the model output, correct?
>> >
>> >
>> > Thank you all,
>> > Simon
>> >
>> > [[alternative HTML version deleted]]
>> >
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