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Title: Joint models for mixed categorical outcomes: a study of HIV risk perception and disease status in Mozambique
Authors: Loquiha, Osvaldo
Hens, Niel
Martins-Fonteyn, Emilia
Meulemans, Herman
Wouters, Edwin
Temmerman, Marleen
Osman, Nafissa
Aerts, Marc
Issue Date: 2017
Citation: Journal of Applied Statistics, 45 (10),p. 1781-1798
Abstract: Two types of bivariate models for categorical response variables are introduced to deal with special categories such as ‘unsure’ or ‘unknown’ in combination with other ordinal categories, while taking additional hierarchical data structures into account. The latter is achieved by the use of different covariance structures for a trivariate random effect. The models are applied to data from the INSIDA survey, where interest goes to the effect of covariates on the association between HIV risk perception (quadrinomial with an ‘unknown risk’ category) and HIV infection status (binary). The final model combines continuation-ratio with cumulative link logits for the risk perception, together with partly correlated and partly shared trivariate random effects for the household level. The results indicate that only age has a significant effect on the association between HIV risk perception and infection status. The proposed models may be useful in various fields of application such as social and biomedical sciences, epidemiology and public health.
Notes: Loquiha, O (reprint author), Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat I BioSt, Agoralaan 1, B-3590 Diepenbeek, Belgium. osvaldo.loquiha@uem.mz
URI: http://hdl.handle.net/1942/25106
DOI: 10.1080/02664763.2017.1391184
ISI #: 000434443400004
ISSN: 0266-4763
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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