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A Comparison of Confidence Interval Methods of Fixed Effect in Nested Error Regression Model

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dc.creator AKDUR, Hatice Tül Kübra
dc.creator ÖZONUR, Deniz
dc.creator BAYRAK, Hülya
dc.date 2016-07-26T00:00:00Z
dc.date.accessioned 2019-07-09T11:59:54Z
dc.date.available 2019-07-09T11:59:54Z
dc.identifier http://dergipark.org.tr/sdufenbed/issue/23916/254902
dc.identifier 10.19113/sdufbed.05095
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/46489
dc.description Linear mixed-effects models are very popular and powerful tools in many scientific fields such as zoology, biology, and education.  Estimators of fixed effects do not only depend on the variances of error terms but they also depend on random terms in mixed-effect models. When the distributions of random effects are unknown or enough sample size cannot be obtained, standard methods may fail. This study aims to determine a promising confidence interval method among existing methods in terms of coverage probability of true value of parameter. Standard and parametric bootstrap-based confidence interval methods for nested error regression model were compared in the simulation study under small samples. It is observed that parametric bootstrap-based method provides better coverage rates for small intra-correlation and profile likelihood method usually provides better results for moderate and strong correlation.
dc.format application/pdf
dc.language en
dc.publisher Süleyman Demirel University
dc.publisher Süleyman Demirel Üniversitesi
dc.relation http://dergipark.org.tr/download/article-file/221148
dc.source Volume: 20, Issue: 2 en-US
dc.source 1308-6529
dc.subject Mixed-effect models; Confidence interval; Parametric bootstrap; Profile likelihood
dc.title A Comparison of Confidence Interval Methods of Fixed Effect in Nested Error Regression Model en-US
dc.type info:eu-repo/semantics/article


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