Re: Multi-level (nested) correlation structures via geepack package

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Re: Multi-level (nested) correlation structures via geepack package

Phat Chau
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


        [[alternative HTML version deleted]]

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Re: Multi-level (nested) correlation structures via geepack package

Bert Gunter-2
You may get lucky, but generally such package-specific questions don't get
responses here. There are about 20000 packages after all. You might do
better posting on the r-sig-mixed-models list or by asking the package
maintainer (?maintainer) whether there is some sort of support list for the
package.

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Sun, Jul 12, 2020 at 9:59 AM Phat Chau <[hidden email]>
wrote:

> 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
>
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

        [[alternative HTML version deleted]]

______________________________________________
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Re: Multi-level (nested) correlation structures via geepack package

dulcalma dulcalma
In reply to this post by Phat Chau
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" <[hidden email]>
To: "[hidden email]" <[hidden email]>; "[hidden email]"
<[hidden email]>
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


        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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Re: Multi-level (nested) correlation structures via geepack package

Phat Chau
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" <[hidden email]> 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" <[hidden email]>
    To: "[hidden email]" <[hidden email]>; "[hidden email]"
    <[hidden email]>
    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
   
   
    [[alternative HTML version deleted]]
   
    ______________________________________________
    [hidden email] mailing list -- To UNSUBSCRIBE and more, see
    https://stat.ethz.ch/mailman/listinfo/r-help
    PLEASE do read the posting guide
    http://www.R-project.org/posting-guide.html
    and provide commented, minimal, self-contained, reproducible code.
   
   
   
   

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.