[R-sig-ME] Course: Introduction to Linear Mixed Effects Models and GLMM with R-INLA

[Henrik Singmann]

But isn't that exactly Mollie's point? You write "Nested data means
multiple observations from the same [unit of observation]". And then she
gave an example where you can have multiple observations from the same unit
of observation without the data being nested.

I also completely agree with her criticism that this terminology is
critical to get right. When I teach mixed models one of the things that
always comes up is that people misunderstand the concept of nested factors:
A factor A is nested in another factor B if certain levels of A only appear
with certain levels of B and not with all levels of B (the latter would be
called crossed). In other words, whether or not we have repeated measures
or multiple observations is unrelated to whether or not there exists
nesting in the data.

Maybe it would make more sense to use "clustered" in that context instead
of "nested".


Am Do., 11. Juni 2020 um 16:20 Uhr schrieb Highland Statistics Ltd <
highstat using highstat.com>:

>
> On 11/06/2020 14:58, Mollie Brooks wrote:
> > The flyer says "Nested data means multiple observations from the same
> > animal, site, area, nest, patient, hospital, vessel,
> > lake, hive, transect, etc.", but this doesn’t agree with my
> > understanding
> > (
> https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#nested-or-crossed). What
>
> > if animals move from one site to another, or patients visit multiple
> > hospitals.
>
> Then it is not nested anymore.
>
>
> > I encounter a lot of scientists who have a misconception of the
> > meaning of nested data, so it would be good to be careful when
> > teaching the terminology. Does R-INLA require random effects to be
> > nested?
>
> No. They can even be spatially correlated....or temporally correlated.
>
> Alain
>
> >
> > Kind regards,
> > Mollie
> >
> >> On 11Jun 2020, at 14:40, Highland Statistics Ltd
> >> <highstat using highstat.com <mailto:highstat using highstat.com>> wrote:
> >>
> >> We would like to announce the following online statistics course:
> >>
> >> Introduction to Linear Mixed Effects Models and GLMM with R-INLA
> >>
> >>
> >> This is an on-demand course with around 35-40 videos (each is 15-60
> >> minutes) with live (optional) Zoom summary sessions scheduled in 2
> >> different time zones:
> >>
> >>  * Time zone 1: 09.00-11.00 British Summer Time.
> >>  * Time zone 2: 19.00-21.00 British Summer Time.
> >>
> >> The course represents around 40 hours of work.
> >>
> >> The course fee includes an (optional) 1-hour face-to-face video chat
> >> with one or both instructors (you can discuss your own data).
> >>
> >> Starting date: 22 June
> >>
> >> Flyer:
> >>
> http://highstat.com/Courses/Flyers/2020/Flyer2020_06_GLMMINLA_Online.pdf
> >>
> >> Website: http://highstat.com/index.php/courses-upcoming
> >>
> >>
> >> Kind regards,
> >>
> >>
> >> Alain Zuur
> >>
> >> --
> >>
> >> Dr. Alain F. Zuur
> >> Highland Statistics Ltd.
> >> 9 St Clair Wynd
> >> AB41 6DZ Newburgh, UK
> >> Email:highstat using highstat.com
> >> URL:www.highstat.com
> >>
> >>
> >> [[alternative HTML version deleted]]
> >>
> >> _______________________________________________
> >> R-sig-mixed-models using r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
> --
>
> Dr. Alain F. Zuur
> Highland Statistics Ltd.
> 9 St Clair Wynd
> AB41 6DZ Newburgh, UK
> Email: highstat using highstat.com
> URL:   www.highstat.com
>
>
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>
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> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>


-- 
Dr. Henrik Singmann
Assistant Professor, Department of Psychology
University of Warwick, UK
http://singmann.org

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