Skip to Main content Skip to Navigation
Journal articles

A note on BIC in mixed-effects models

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.
Complete list of metadatas

Cited literature [27 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00991708
Contributor : Marc Lavielle <>
Submitted on : Tuesday, March 3, 2015 - 12:53:04 PM
Last modification on : Wednesday, September 16, 2020 - 4:05:09 PM
Long-term archiving on: : Thursday, June 4, 2015 - 10:05:31 AM

File

BIC_DelattreLaviellePoursat.pd...
Publisher files allowed on an open archive

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Maud Delattre, Marc Lavielle, Marie-Anne Poursat. A note on BIC in mixed-effects models. Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2014, 8, pp.456--475. ⟨10.1214/14-EJS890⟩. ⟨hal-00991708⟩

Share

Metrics

Record views

408

Files downloads

1191