Predicting health programme participation: A gravity‐based, hierarchical modelling approach
Data(s) |
10/08/2015
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Resumo |
Statistical analyses of health program participation seek to address a number of objectives compatible with the evaluation of demand for current resources. In this spirit, a spatial hierarchical model is developed for disentangling patterns in participation at the small area level, as a function of population-based demand and additional variation. For the former, a constrained gravity model is proposed to quantify factors associated with spatial choice and account for competition effects, for programs delivered by multiple clinics. The implications of gravity model misspecification within a mixed effects framework are also explored. The proposed model is applied to participation data from a no-fee mammography program in Brisbane, Australia. Attention is paid to the interpretation of various model outputs and their relevance for public health policy. |
Formato |
application/pdf application/pdf |
Identificador | |
Publicador |
Wiley-Blackwell Publishing Ltd. |
Relação |
http://eprints.qut.edu.au/90762/1/WhiteMengersenJRSSC_main.pdf http://eprints.qut.edu.au/90762/2/WhiteMengersenJRSSCsupplementary.pdf http://onlinelibrary.wiley.com/doi/10.1111/rssc.12111/abstract DOI:0.1111/rssc.12111 White, Nicole & Mengersen, Kerrie (2015) Predicting health programme participation: A gravity‐based, hierarchical modelling approach. Journal of the Royal Statistical Society: Series C (Applied Statistics). (In Press) CRCSI/4.42 |
Direitos |
Copyright 2015 Royal Statistical Society |
Fonte |
ARC Centre of Excellence for Mathematical & Statistical Frontiers (ACEMS); Science & Engineering Faculty; Mathematical Sciences |
Palavras-Chave | #010401 Applied Statistics #Spatial modelling #Health services research #Bayesian statistics |
Tipo |
Journal Article |