This review examines the state of Bayesian thinking as Statistics in Medicine was launched
in 1982, reflecting particularly on its applicability and uses in medical research. It then looks …

Modelling based on finite mixture distributions is a rapidly developing area with the range of
applications exploding. Finite mixture models are nowadays applied in such diverse areas …

While mapped data provide a common ground for discussions between the public, the
media, regulatory agencies, and public health researchers, the analysis of spatially …

Since the publication of the second edition, many new Bayesian tools and methods have
been developed for space-time data analysis, the predictive modeling of health outcomes …

Spatial epidemiology is the description and analysis of the geographical distribution of
disease. It is more important now than ever, with modern threats such as bio-terrorism …

Disease mapping involves the analysis of geo-referenced disease incidence data and has
many applications, for example within resource allocation, cluster alarm analysis, and …

For frequency counts, the situation of extra zeros often arises in biomedical applications.
This is demonstrated with count data from a dental epidemiological study in Belo Horizonte …

This contribution reviews some of the major developments in the algorithmic area connected
with the construction of maximum likelihood estimators in semiparametric mixture models …

An interesting epidemiological problem is the analysis of geographical variation in rates of
disease incidence or mortality. One goal of such an analysis is to detect clusters of elevated …

Patients are not alike! This simple truth is often ignored in the analysis of me-cal data, since
most of the time results are presented for the “average” patient. As a result, potential …