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

[Marc Schwartz]

> On Jul 2, 2019, at 8:58 AM, Heather H Kettrey <hkettre using 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