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- 2Conditional autoregressive
- 2Generalized linear mixed model
- 2Geographic epidemiology
- 1Disease mapping
- 1Generalized estimating equation
- 1Penalized quasi-likelihood
This paper studies generalized linear mixed models (GLMMs) for the analysis of geographic and temporal variability of disease rates. This class of models adopts spatially correlated random effects and random temporal components. Spatio-temporal models that use conditional autoregressive smoothing...
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....