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

[Viechtbauer, Wolfgang (SP)]

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 using r-project.org] On Behalf Of Heather H Kettrey
Sent: Tuesday, 02 July, 2019 14:59
To: r-help using 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