The hazard function plays a central role in survival analysis. In a homogeneous population,
the distribution of the time to event, described by the hazard, is the same for each individual …

The continuously increasing cost of the US healthcare system has received significant
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …

The concept of frailty offers a convenient way to introduce unobserved heterogeneity and
associations into models for survival data. In its simplest form, frailty is an unobserved …

In many cancer studies, the main outcome under assessment is the time to an event of
interest. The generic name for the time is survival time, although it may be applied to the time …

This book provides an accessible approach to Bayesian computing and data analysis, with
an emphasis on the interpretation of real data sets. Following in the tradition of the …

Background Highly active antiretroviral therapy (HAART) is being scaled up in developing
countries. We compared baseline characteristics and outcomes during the first year of …

Since the early 1980s, the econometric analysis of duration variables has become
widespread. This chapter provides an overview of duration analysis, with an emphasis on …

The paper presents a comprehensive investigation of the behaviour of carsharing members
through the analysis of administrative datasets of a dominant carsharing program in Toronto …

Modern health data science applications leverage abundant molecular and electronic health
data, providing opportunities for machine learning to build statistical models to support …

In the analysis of survival data arising in clinical trials, Cox's proportional hazards regression
model (or equivalently in the case of two treatment groups, the log-rank test) is firmly …