|
Abstract
|
Overdispersion and structural zeros are two major manifestations of departure from the Poisson assumption when modeling count responses using Poisson loglinear regression. Ignoring such departures could yield bias and lead to wrong conclusions. Different approaches have been developed to tackle these two major problems. In this talk, we review available methods for dealing with overdispersion and structural zeros within a longitudinal data setting and propose a new semi-parametric modeling approach to address the limitations of these methods. We illustrate our approach with both simulated and real study data.
|
