Hi Duncan,
Thank you for your message. All of those citations and suggestions are
wonderful and highly relevant for GEEs. My concern is that I need
multi-level/nested correlation structures, whereas those handle the
specification of covariance matrices at the level of repeated observations
within-subject. I think the paper attached contains the theory behind such
nested correlation structures, but the coding for it is not as apparent.
Edward
On 2020-07-12, 11:06 PM, "dulcalma dulcalma" <dulca...@bigpond.com> wrote:
Hi
Your choice of package should partly depend on the type of dependent
variable or Y that you are going to be dealing with
categorical/ordinal data may involve different packages than continuous
or binary data see multgee for one.
The number of samples can also make a difference GEE with the "correct
model" should normally have no problems with numbers 30-40; 25 or less
would normally require corrections and a diffence package.
The doi for multgee paper is 10.1111/biom.12054 and Touloumis paper in
Journal of Statistical Software
For longitudinal data there is the following doi:
10.2307/2531248
and
10.1097/EDE.0b013e3181caeb90
10.1093/biomet/90.1.29
10.1007/s00362-017-0881-0
10.1002/sim.2368
a search for gee in the list of available packages should show you the
alternatives.
As a check of the result do the statistics on another package. I
remember doing a simple gee with an example
from a book using 4 different packages 2 of which gave poor or
unreasonable answers
Regards
Duncan
Duncan Mackay
Department of Agronomy and Soil Science
University of New England
ARMIDALE NSW 2351
------ Original Message ------
From: "Phat Chau" <phat.c...@mail.utoronto.ca>
To: "r-help@R-project.org" <r-help@R-project.org>; "sor...@math.aau.dk"
<sor...@math.aau.dk>
Sent: Sunday, 12 Jul, 2020 At 11:52 PM
Subject: Re: [R] Multi-level (nested) correlation structures via
geepack package
Hello,
I have a multi-level, cohort dataset with three levels: repeat measures
of a response (level 1), that are collected from individual participants
(level 2) who are students within a school (level 3). I would like to do
a generalized estimating equation (GEE) analysis of this clustered data,
but to do so I need to specify ‘nested’ correlation structures (e.g.
exchangeable, compound symmetric, Toeplitz) to account for the
within-individual and within-cluster correlations.
Here is a reference paper that describes a nested exchangeable
correlation structure and nested compound symmetry:
doi:10.1111/j.1541-0420.2009.01374.x.
The geepack is available in R to do GEE analyses, but it seems to me
that it only allows the user to specify a correlation structure via the
geepack(…‘corstr = ‘) option which only accounts for the
within-individual correlations (that arise from repeated measures).
Would it be possible to specify the nested correlation structures that I
refer to here to also account for the within-cluster correlations using
this package?
Thank you,
Edward
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