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

被引：4

作者：

Cantoni, Eva ^{[1
,2
]}

Jacot, Nadege ^{[3
,4
]}

Ghsletta, Paolo ^{[5
,6
]}

机构：

[1] Univ Geneva, Res Ctr Stat, Geneva, Switzerland

[2] Univ Geneva, Geneva Sch Econ & Management, Geneva, Switzerland

[3] Univ Geneva, Res Ctr Stat, Geneva Sch Econ & Management, Geneva, Switzerland

[4] Univ Geneva, Fac Psychol & Educ Sci, Geneva, Switzerland

[5] Univ Geneva, Swiss Distance Univ Inst, Fac Psychol & Educ Sci, Fac Psychol, Brig, Switzerland

[6] Univ Geneva, Swiss Natl Ctr Competence Res LIVES, Geneva, Switzerland

来源：

ECONOMETRICS AND STATISTICS | 2024年 / 29卷

关键词：

Linear mixed-effects model; Explained variation; Model adequacy; Model selection; GOODNESS-OF-FIT; VARIABLE SELECTION; AKAIKE INFORMATION; BAYESIAN MEASURES; LIKELIHOOD; R-2; VARIANCE;

D O I：

10.1016/j.ecosta.2021.05.005

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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. 1 (c) 2021 The Authors. Published by Elsevier B.V. on behalf of EcoSta Econometrics and Statistics. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )

引用

页码：150 / 168

页数：19