[R] Multi-level (nested) correlation structures via geepack package
ph@t@ch@u @end|ng |rom m@||@utoronto@c@
Mon Jul 13 17:40:56 CEST 2020
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.
On 2020-07-12, 11:06 PM, "dulcalma dulcalma" <dulcalma using bigpond.com> wrote:
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:
a search for gee in the list of available packages should show you the
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
Department of Agronomy and Soil Science
University of New England
ARMIDALE NSW 2351
------ Original Message ------
From: "Phat Chau" <phat.chau using mail.utoronto.ca>
To: "r-help using R-project.org" <r-help using R-project.org>; "sorenh using math.aau.dk"
<sorenh using math.aau.dk>
Sent: Sunday, 12 Jul, 2020 At 11:52 PM
Subject: Re: [R] Multi-level (nested) correlation structures via
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:
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
[[alternative HTML version deleted]]
R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
PLEASE do read the posting guide
and provide commented, minimal, self-contained, reproducible code.
More information about the R-help