Empirical performance of estimation methods in Beta mixed models with application to ecological data

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AuteurLOKONON, BRUNO E
AuteurDJIBRIL MOUSSA, FREEDATH LAYE ERI YOMI
AuteurSALIOU, DIOUF
AuteurGLELE KAKAI, A ROMAIN LUCAS
Date d'ajout2026-06-02T16:06:57Z
Date de disponibilite2026-06-02T16:06:57Z
Date de publication2020
ResumeThis study uses a Monte Carlo simulation design to assess the performance of Beta and linear mixed models on bounded response variables through comparison of four estimation methods. Four factors affecting the performance of the estimation methods were considered: the number of groups, the number of observations per group, the variance and distribution of the random effects. Our results showed that, for small number of groups (less than 30), the Beta mixed model outperformed the linear mixed model whatever the size of the groups. In the case of a large number of groups (superior or equal to 30), both approaches showed relatively close performance. The results from the simulation study have been illustrated with real life data.
DOI10.16929/as/2020.2279.159
Autre identifiantBECDB-14927
URIhttps://dspace.uac.bj/handle/123456789/12693
Languefr
Fait partie deAfrika Statistika
SujetBeta distribution
Sujetcontinuous proportion
Sujettransformations
Sujethierarchical
Sujetmodelling
Sujetperformance
SujetApplication
TitreEmpirical performance of estimation methods in Beta mixed models with application to ecological data
TypeArticle

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