The National Cancer Institute (NCI) suggests a sudden reduction in prostate cancer mortality rates, likely due to highly successful treatments and screening methods for early diagnosis. We are interested in understanding the impact of medical breakthroughs, treatments, or interventions, on the...

Cancer maps are important tools in the descriptive presentation of the cancer burden. The objective is to explore the advantages and disadvantages of mapping methods based on point data in comparison with maps based on aggregated data. Four types of maps were prepared based on the same...

Extended Poisson process modelling is generalised to allow for covariate-dependent dispersion as well as a covariate-dependent mean response. This is done by a re-parameterisation that uses approximate expressions for the mean and variance. Such modelling allows under- and over-dispersion, or a...

In this paper, a generalization of the two-parameter partial credit model (2PL-PCM) and of two special cases, the partial credit model (PCM) and the rating scale model (RSM), with a hierarchical data structure will be presented. Having shown how 2PL-PCM, as with other item response theory (IRT)...

We analyse data on abortion rate (AR) in Italy with a particular focus on different behaviours in different regions in Italy. The aim is to try to reveal the relationship between the AR and several covariates that describe in some way the modernity of the region and the condition of the women...

Consistency of propensity score matching estimators hinges on the propensity score's ability to balance the distributions of covariates in the pools of treated and non-treated units. Conventional balance tests merely check for differences in covariates’ means, but cannot account for...

In this work, we show that the Dagum distribution [3] may be a competitive model for describing data which include censored observations in lifetime and reliability problems. Maximum likelihood estimates of the three parameters of the Dagum distribution are determined from samples with type I...

A class of mixture models in which a component is associated with an improper distribution is introduced. This component is intended mainly for outliers. The models are motivated by the EM algorithm, and are fitted by its simple adaptation. They are illustrated on several examples with large...