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Scientific article
Open access
English

Review and comparison of measures of explained variation and model selection in linear mixed-effects models

Published inEconometrics and statistics, vol. 29, p. 150-168
Publication date2024
First online date2021-06-02
Abstract

In linear mixed-effects models, several frequentist and Bayesian measures have been proposed to evaluate model adequacy or/and to perform model selection. First, a large set of these measures are selected, presented with comparable notations, discussed in their strengths, weaknesses, and applicability range, and finally commented upon regarding their limitations. Then, these measures are illustrated on the home radon levels data (Gelman & Pardoe, Technometrics, 241-251, 48, 2006). Next, an extensive simulation study is carried out, to evaluate their sensitivity in selecting the correct model from a series of simpler models containing fewer parameters. Finally, recommendations on the use of these different measures are provided.

eng
Keywords
  • Linear mixed-effects model
  • Explained variation
  • Model adequacy
  • Modelselection
Research group
Citation (ISO format)
CANTONI, Eva, JACOT, Nadège, GHISLETTA, Paolo. Review and comparison of measures of explained variation and model selection in linear mixed-effects models. In: Econometrics and statistics, 2024, vol. 29, p. 150–168. doi: 10.1016/j.ecosta.2021.05.005
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Article (Published version)
Article (Accepted version)
accessLevelPrivate
Identifiers
ISSN of the journal2452-3062
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Technical informations

Creation06/22/2021 9:03:00 PM
First validation06/22/2021 9:03:00 PM
Update time04/29/2024 3:15:55 PM
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