Bayesian model selection for multilevel mediation models

被引:2
作者
Ariyo, Oludare [1 ,2 ]
Lesaffre, Emmanuel [1 ]
Verbeke, Geert [1 ]
Huisman, Martijn [3 ]
Heymans, Martijn [3 ,4 ]
Twisk, Jos [3 ]
机构
[1] Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat I BioSt, Leuven, Belgium
[2] Fed Univ Agr, Dept Stat, Abeokuta, Nigeria
[3] Amsterdam UMC, Amsterdam Publ Hlth Res Inst, Dept Epidemiol & Data Sci, Amsterdam, Netherlands
[4] Vrije Univ Amsterdam, Dept Sociol, Amsterdam, Netherlands
关键词
deviance information criterion; marginalized likelihood; multilevel mediation models; pseudo Bayes factor; Watanabe-Akaike information criterion; DEVIANCE INFORMATION CRITERION; MODERATED MEDIATION; CONFIDENCE-LIMITS; EQUIVALENCE; ADVANTAGES; PRODUCT;
D O I
10.1111/stan.12256
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Mediation analysis is often used to explore the complex relationship between two variables through a third mediating variable. This paper aims to illustrate the performance of the deviance information criterion, the pseudo-Bayes factor, and the Watanabe-Akaike information criterion in selecting the appropriate multilevel mediation model. Our focus will be on comparing the conditional criteria (given random effects) versus the marginal criteria (averaged over random effects) in this respect. Most of the previous work on the multilevel mediation models fails to report the poor behavior of the conditional criteria. We demonstrate here the superiority of the marginal version of the selection criteria over their conditional counterpart in the mediated longitudinal settings through simulation studies and via an application to data from the Longitudinal Aging Study of the Amsterdam study. In addition, we demonstrate the usefulness of our self-written R function for multilevel mediation models.
引用
收藏
页码:219 / 235
页数:17
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