On 11Jun 2020, at 17:04, John Poe <jdpoe223 at gmail.com> wrote:
I think it's a little bit pedantic to criticize the flyer here since I
assume that the distinction between nested and cross classified grouping
structures is made pretty clear in the class itself.
I haven't seen the course material obviously so that's an assumption on my
part given how I teach it. I do spend a lot of time on it whenever I teach
mixed effects models because it is an important point of confusion for
people. I tend to use either "clustered" or the term "grouping structure"
as generic and differentiate between nested, crossed, and multiple
membership personally. So i understand the point Mollie and Henrik are
making but it might be unfair to expect that level of nuance in a flyer?
On Thu, Jun 11, 2020, 10:51 AM Henrik Singmann <singmann at gmail.com> wrote:
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 at 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
(
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
On 11Jun 2020, at 14:40, Highland Statistics Ltd
<highstat at highstat.com <mailto:highstat at 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:
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 at highstat.com
URL:www.highstat.com
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