Modelling mortality rates using GEE models

Abstract

Generalised estimating equation (GEE) models are extensions of generalised linear models by relaxing the assumption of independence. These models are appropriate to analyze correlated longitudinal responses which follow any distribution that is a member of the exponential family. This model is used to relate daily mortality rate of Maltese adults aged 65 years and over with a number of predictors, including apparent temperature, season and year. To accommodate the right skewed mortality rate distribution a Gamma distribution is assumed. An identity link function is used for ease of interpretating the parameter estimates. An autoregressive correlation structure of order 1 is used since correlations decrease as distance between observations increases. The study shows that mortality rate and temperature are related by a quadratic function. Moreover, the GEE model identifies a number of significant main and interaction effects which shed light on the effect of weather predictors on daily mortality rates.