R help - Jul 2019 - Conditional Logistic Regression with Multilevel Data [using clogistic() in Epi and lmer() in lme4???]

I need to run some conditional logistic regression models on a multilevel
matched dataset (propensity score matched data from multiple research sites).


I can pretty easily use the clogistic() function in the Epi package to run
conditional logistic regression models on each separate/nested subset of the
data (e.g., data obtained from each research site separately). However, I cannot
figure out how to run an aggregate analysis (of all aggregated sites) in a way
that accounts for clustering.


When using unconditional logistic regression I can run the aggregate analysis
lmer() function in the lme4 package. However, I cannot figure out how to run
conditional logistic regression with the lmer() function (I am also open to any
other packages/functions that might work).


Thanks in advance for help with this.


Heather Hensman Kettrey, PhD

Assistant Professor of Sociology

Clemson University

	[[alternative HTML version deleted]]

> an aggregate analysis (of all aggregated sites) in a way that accounts
for clustering

I'm not familiar with this topic.
For the benefit of those of us (like me), who are not experts on
conditional logistic regression, what does the above statement mean?

Hopefully, someone who is more familiar with this topic, can help you more.

	[[alternative HTML version deleted]]

> On Jul 2, 2019, at 8:58 AM, Heather H Kettrey <hkettre at
clemson.edu> wrote:
> 
> I need to run some conditional logistic regression models on a multilevel
matched dataset (propensity score matched data from multiple research sites).
> 
> 
> I can pretty easily use the clogistic() function in the Epi package to run
conditional logistic regression models on each separate/nested subset of the
data (e.g., data obtained from each research site separately). However, I cannot
figure out how to run an aggregate analysis (of all aggregated sites) in a way
that accounts for clustering.
> 
> 
> When using unconditional logistic regression I can run the aggregate
analysis lmer() function in the lme4 package. However, I cannot figure out how
to run conditional logistic regression with the lmer() function (I am also open
to any other packages/functions that might work).
> 
> 
> Thanks in advance for help with this.
> 
> 
> Heather Hensman Kettrey, PhD
> 
> Assistant Professor of Sociology
> 
> Clemson University

A search does not seem to yield specific examples that are relevant.

That being said, it might be worthwhile posting to r-sig-mixed-models:

  https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

where experts in the domain of multi-level models reside.

There may be an approach using glmer() or an alternative package, where you can
define the paired observations within sites in manner that makes sense for the
clustering of data at the site level.

Regards,

Marc Schwartz

This is off topic. This list is about R programming, not statistics. The OP
should consult statistical resources, such as stats.stackexchange.com  .

Bert

On Tue, Jul 2, 2019, 6:22 PM Abby Spurdle <spurdle.a at gmail.com> wrote:
> > an aggregate analysis (of all aggregated sites) in a way that accounts
> for clustering
>
> I'm not familiar with this topic.
> For the benefit of those of us (like me), who are not experts on
> conditional logistic regression, what does the above statement mean?
>
> Hopefully, someone who is more familiar with this topic, can help you more.
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org 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]]

Dear Heather,

You can do this with clogit() from the 'survival' package, using
strata(). See:

http://www.metafor-project.org/doku.php/tips:clogit_paired_binary_data

You can also use lme4::glmer(), glmmML::glmmML(), or metafor::rma.glmm() for
that. [1]

[1] Rerunning this example, I noticed a slight issue with the structuring of the
output from rma.glmm() -- if you want to run that example, install the
'devel' version of metafor as described here:

https://wviechtb.github.io/metafor/#installation

Best,
Wolfgang

-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Heather H
Kettrey
Sent: Tuesday, 02 July, 2019 14:59
To: r-help at r-project.org
Subject: [R] Conditional Logistic Regression with Multilevel Data [using
clogistic() in Epi and lmer() in lme4???]

I need to run some conditional logistic regression models on a multilevel
matched dataset (propensity score matched data from multiple research sites).

I can pretty easily use the clogistic() function in the Epi package to run
conditional logistic regression models on each separate/nested subset of the
data (e.g., data obtained from each research site separately). However, I cannot
figure out how to run an aggregate analysis (of all aggregated sites) in a way
that accounts for clustering.

When using unconditional logistic regression I can run the aggregate analysis
lmer() function in the lme4 package. However, I cannot figure out how to run
conditional logistic regression with the lmer() function (I am also open to any
other packages/functions that might work).

Thanks in advance for help with this.

Heather Hensman Kettrey, PhD
Assistant Professor of Sociology
Clemson University

Wolfgang,

Perhaps I am missing something here, but with clogit(), or Heather's initial
attempt at using clogistic(), as both have 'strata' arguments,
wouldn't the 'strata' argument need to be able to accept a nested
structure, along the lines of strata(id / site)?

On the page that you link to below, I don't see an example of that type of
nesting structure.

The mixed effects models would generally support a nested random effects
specification, if that makes sense here.

Regards,

Marc Schwartz

> On Jul 3, 2019, at 4:41 AM, Viechtbauer, Wolfgang (SP)
<wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
> 
> Dear Heather,
> 
> You can do this with clogit() from the 'survival' package, using
strata(). See:
> 
> http://www.metafor-project.org/doku.php/tips:clogit_paired_binary_data
> 
> You can also use lme4::glmer(), glmmML::glmmML(), or metafor::rma.glmm()
for that. [1]
> 
> [1] Rerunning this example, I noticed a slight issue with the structuring
of the output from rma.glmm() -- if you want to run that example, install the
'devel' version of metafor as described here:
> 
> https://wviechtb.github.io/metafor/#installation
> 
> Best,
> Wolfgang
> 
> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Heather
H Kettrey
> Sent: Tuesday, 02 July, 2019 14:59
> To: r-help at r-project.org
> Subject: [R] Conditional Logistic Regression with Multilevel Data [using
clogistic() in Epi and lmer() in lme4???]
> 
> I need to run some conditional logistic regression models on a multilevel
matched dataset (propensity score matched data from multiple research sites).
> 
> I can pretty easily use the clogistic() function in the Epi package to run
conditional logistic regression models on each separate/nested subset of the
data (e.g., data obtained from each research site separately). However, I cannot
figure out how to run an aggregate analysis (of all aggregated sites) in a way
that accounts for clustering.
> 
> When using unconditional logistic regression I can run the aggregate
analysis lmer() function in the lme4 package. However, I cannot figure out how
to run conditional logistic regression with the lmer() function (I am also open
to any other packages/functions that might work).
> 
> Thanks in advance for help with this.
> 
> Heather Hensman Kettrey, PhD
> Assistant Professor of Sociology
> Clemson University