Stanova: A Smoothed-Anova-Based Model for Spatio-Temporal Disease Mapping

Spatio-temporal disease mapping can be viewed as a multivariate disease mapping problem with a given order of the geographic patterns to be studied. As a consequence, some of the techniques in multivariate literature could also be used to build spatio-temporal models. In this paper we propose using the smoothed ANOVA multivariate model for spatio-temporal problems. Under our approach the time trend for each geographic unit is modeled parametrically, projecting it on a preset orthogonal basis of functions (the contrasts in the smoothed ANOVA nomenclature), while the coefficients of these projections are considered to be spatially dependent random effects. Despite the parametric temporal nature of our proposal, we show with both simulated and real datasets that it may be as flexible as other spatio-temporal smoothing models proposed in the literature and may model spatio-temporal data with several sources of variability. © 2014, Springer-Verlag Berlin Heidelberg.