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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16113

Title: Modeling heterogeneity for count data: A study of maternal mortality in health facilities in Mozambique
Authors: LOQUIHA, Osvaldo
HENS, Niel
Chavane, Leonardo
Temmerman, Marleen
Issue Date: 2013
Citation: BIOMETRICAL JOURNAL, 55 (5), p. 647-660
Abstract: Count data are very common in health services research, and very commonly the basic Poisson regression model has to be extended in several ways to accommodate several sources of heterogeneity: (i) an excess number of zeros relative to a Poisson distribution, (ii) hierarchical structures, and correlated data, (iii) remaining unexplained sources of overdispersion. In this paper, we propose hierarchical zero-inflated and overdispersed models with independent, correlated, and shared random effects for both components of the mixture model. We show that all different extensions of the Poisson model can be based on the concept of mixture models, and that they can be combined to account for all different sources of heterogeneity. Expressions for the first two moments are derived and discussed. The models are applied to data on maternal deaths and related risk factors within health facilities in Mozambique. The final model shows that the maternal mortality rate mainly depends on the geographical location of the health facility, the percentage of women admitted with HIV and the percentage of referrals from the health facility.
Notes: Aerts, M (reprint author), Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat I Biost, Agoralaan 1, B-3590 Diepenbeek, Belgium, marc.aerts@uhasselt.be
URI: http://hdl.handle.net/1942/16113
DOI: 10.1002/bimj.201200233
ISI #: 000327816900001
ISSN: 0323-3847
Category: A1
Type: Journal Contribution
Validation: ecoom, 2014
Appears in Collections: Research publications

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