Multi-level (nested) correlation structures via geepack package

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

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.chau at mail.utoronto.ca>
    To: "r-help at R-project.org" <r-help at R-project.org>; "sorenh at math.aau.dk" 
    <sorenh at 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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