Recurrent events are important in scientific as well as everyday contexts. These are events that may occur repeatedly over time, and which generally carry either a positive or negative connotation. For example, repeated attacks of asthma for an individual, repeated insurance claims for a company, or repeated breakdowns in equipment of systems, have negative implications. The Statistical Analysis of Recurrent Events describes how to model, collect and analyse data on recurrent events, in order to understand them better and improve processes in which they occur. Applications in areas such as cancer treatment, chronic disease and equipment reliability are discussed at length in the book, including details on how to implement analyses using available software.

Provides an extensive discussion of the wide range of models and methods that are available to researchers and practitioners faced with the design and analysis of studies involving recurrent events

Autorentext
Jerald F. Lawless, PhD, is a professor and holder of the General Motors Canada-NSERC Industrial Research Chair in the Department of Statistics & Actuarial Science at the University of Waterloo, Ontario, Canada.

Inhalt
Models and Frameworks for Analysis of Recurrent Events.- Methods Based on Counts and Rate Functions.- Analysis of Gap Times.- General Intensity-Based Models.- Multitype Recurrent Events.- Observation Schemes Giving Incomplete or Selective Data.- OtherTopics.