Chapter 7 Spatio-temporal modeling of areal data. Lung cancer in Ohio

Learning objectives:

Risk of lung cancer in Ohio, USA, from 1968 to 1988 using the R-INLA package:

• how to calculate the expected disease counts using indirect standardization, and the standardized incidence ratios (SIRs).

• how to fit a Bayesian spatio-temporal model to obtain disease risk estimates for each of the Ohio counties and years of study.

• how to create static and interactive maps and time plots of the SIRs and disease risk estimates.