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Permanent link (DOI): https://doi.org/10.7939/R3HD7NS4D

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Spatio-temporal modelling using B-spline for disease mapping: analysis of childhood cancer trends Open Access

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Author or creator
Torabi, Mahmoud
Rosychuk, Rhonda J.
Additional contributors
Subject/Keyword
geographic epidemiology
conditional autoregressive
penalized quasi-likelihood
disease mapping
generalized linear mixed model
Type of item
Journal Article (Published)
Language
English
Place
Time
Description
To analyze childhood cancer diagnoses in the province of Alberta, Canada during 1983-2004, we construct a generalized linear mixed model for the analysis of geographic and temporal variability of cancer rates. In this model, spatially correlated random e®ects and temporal components are adopted. The interaction between space and time is also accommodated. Spatio-temporal models that use conditional autoregressive smoothing across the spatial di- mension and B-spline over the temporal dimension are considered. We study the patterns of incidence rates over time and identify areas with consistently high rate estimates as areas for further investigation. We apply the method of penalized quasi-likelihood to estimate the model parameters. We illustrate this approach using a yearly data set of childhood cancer diagnoses in the province of Alberta, Canada during 1983-2004.
Date created
2011
DOI
doi:10.7939/R3HD7NS4D
License information
Creative Commons Attribution-Non-Commercial-No Derivatives 3.0 Unported
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Citation for previous publication
Torabi M, Rosychuk RJ (2011). Spatio-temporal Modeling Using B-spline for Disease Mapping: Analysis of Childhood Cancer Trends. Journal of Applied Statistics, 38(9), 1769-1781.
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