Predicting health programme participation: A gravity‐based, hierarchical modelling approach


Autoria(s): White, Nicole; Mengersen, Kerrie
Data(s)

10/08/2015

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

http://eprints.qut.edu.au/90762/

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