Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 8, Number 1 (2014), 456-475.
A note on BIC in mixed-effects models
Maud Delattre, Marc Lavielle, and Marie-Anne Poursat
Abstract
The Bayesian Information Criterion (BIC) is widely used for variable selection in mixed effects models. However, its expression is unclear in typical situations of mixed effects models, where simple definition of the sample size is not meaningful. We derive an appropriate BIC expression that is consistent with the random effect structure of the mixed effects model. We illustrate the behavior of the proposed criterion through a simulation experiment and a case study and we recommend its use as an alternative to various existing BIC versions that are implemented in available software.
Article information
Source
Electron. J. Statist., Volume 8, Number 1 (2014), 456-475.
Dates
First available in Project Euclid: 2 May 2014
Permanent link to this document
https://projecteuclid.org/euclid.ejs/1399035845
Digital Object Identifier
doi:10.1214/14-EJS890
Mathematical Reviews number (MathSciNet)
MR3200764
Zentralblatt MATH identifier
1348.62186
Subjects
Primary: 62J02: General nonlinear regression 62J12: Generalized linear models
Keywords
Bayesian Information Criterion BIC mixed effects model variable selection
Citation
Delattre, Maud; Lavielle, Marc; Poursat, Marie-Anne. A note on BIC in mixed-effects models. Electron. J. Statist. 8 (2014), no. 1, 456--475. doi:10.1214/14-EJS890. https://projecteuclid.org/euclid.ejs/1399035845