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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