[R-sig-ME] var(ranef(Random Effect)) not the same as the variance component
Ben Bolker
bbo|ker @end|ng |rom gm@||@com
Tue Sep 8 03:24:34 CEST 2020
On 9/7/20 9:22 PM, Simon Harmel wrote:
> 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)?
I would probably say something like "incorporating among-subject
variation in that term (e.g., the initial status) in the model". Or
"accounting for".
>
> On Mon, Sep 7, 2020 at 7:53 PM Simon Harmel <sim.harmel using gmail.com
> <mailto: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
> <mailto: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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