Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications

Survival data typically consist of a single event for each population unit, namely, end of life, which is modeled with a life distribution. In contrast, many applications involve repeated-events data, where a sample unit may accumulate any number of events over time. Examples include the number and cost of repairs of products, the number and treatment costs of recurrent disease episodes in patients, and the number and costs of childbirths, divorces, etc. Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications provides basic nonparametric methods for such data, especially the plot of the nonparametric estimate of the population mean cumulative function (MCF), which yields most of the information sought. An introduction, this book provides a unified presentation of graphical analysis of repeated-events data for practitioners. It is the first book to present a simple unified theory that includes data on "costs" or other "values" of discrete events, not just the number of recurrent events. It surveys computer programs that calculate and plot the MCF estimate with confidence limits, shows their output, and explains how to interpret such plots. Many such calculations can be easily done with a pocket calculator or spreadsheet program. In addition, the book provides methods for accumulated variables that vary continuously with time, and it briefly introduces basic regression models (Poisson, Cox) and parametric models (homogeneous and nonhomogeneous Poisson processes and renewal processes).