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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 |
Files in This Item:
File | Description | Size | Format | |
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rakhmawati 1.pdf Restricted Access | Published version | 1.37 MB | Adobe PDF | View/Open Request a copy |
locinfNL21.pdf Restricted Access | Peer-reviewed author version | 3.19 MB | Adobe PDF | View/Open Request a copy |
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