The Bayesian approach to statistical analysis has many theoretical advantages, but in the past, its use has been limited by a lack of suitable statistical software. In a book published this year by Stata Press called Bayesian Analysis with Stata, I have tried to show that Stata can be used for...

The Cox proportional hazards model is one of the most popular methods for analyzing survival or failure-time data. The key assumption underlying the Cox model is that of proportional hazards. This assumption may often be violated in practice. Transformation survival models extend the Cox...

This paper presents a parametric counter-factual model identifying average treatment effects (ATEs) by conditional mean independence when externality (or neighborhood) effects are incorporated within the traditional Rubin-potential outcome model. As such, it tries to generalize the usual...

The time-stratified case-crossover design is widely used in environmental epidemiology to analyze the short-term effects of environmental risk factors, such as air pollution or temperature, on human health. It compares the exposure level in the day when the health event occurs (case day) with...

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The minimum density power divergence (MDPD) framework (Basu et al., 1998) provides a family of estimators indexed by a parameter (α), which controls the tradeoff between efficiency and robustness. In this paper, we extend this estimation framework to finite mixtures of regression models. In...

Cancer registries are often interested in estimating net survival, the probability of survival if the cancer under study is the only possible cause of death. In 2011, Pohar Perme et al. proposed a new estimator of net survival based on inverse-probability weighting. They demonstrated that...