Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/26265
Title: Local influence diagnostics for hierarchical finite-mixture random-effects models
Authors: RAKHMAWATI, Trias Wahyuni 
MOLENBERGHS, Geert 
VERBEKE, Geert 
FAES, Christel 
Issue Date: 2018
Source: BIOMETRICAL JOURNAL, 60(2), p. 369-380
Abstract: The main objective of this paper is to evaluate the influence of individual subjects exerted on a random-effects model for repeated measures, where the random effects follow a mixture distribution. The diagnostic tool is based on local influence with perturbation scheme that explicitly targets influences resulting from perturbing the mixture component probabilities. Bruckers, Molenberghs, Verbeke, and Geys (2016) considered a similar model, but focused on influences stemming from perturbing a subject's likelihood contributions as a whole. We also compare the two types of perturbation. Our results are illustrated using linear mixed models fitted to data from three studies. A simulation study is also conducted in order to strengthen the result from case studies.
Notes: Rakhmawati, TW (reprint author), Hasselt Univ, I BioStat, B-3500 Hasselt, Belgium, triaswahyuni.rakhmawati@uhasselt.be
Keywords: local influence; mixture model for random-effects; perturbation
Document URI: http://hdl.handle.net/1942/26265
ISSN: 0323-3847
e-ISSN: 1521-4036
DOI: 10.1002/bimj.201600203
ISI #: 000426492900011
Category: A1
Type: Journal Contribution
Validations: ecoom 2019
Appears in Collections:Research publications

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