Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications: Series Number 10 (ASA-SIAM Series on Statistics and Applied Probability, Series Number 10) - Hardcover

Nelson, Wayne B.

 
9780898715224: Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications: Series Number 10 (ASA-SIAM Series on Statistics and Applied Probability, Series Number 10)

Synopsis

Survival data 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 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 of childbirths to statisticians. This applied book provides practitioners with basic nonparametric methods for such data, particularly the plot of the estimate of the population mean cumulative function (MCF), which yields most of the information sought. Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications 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 events.

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Review

'The book is clearly written, to the point, and is easy to read. It is well suited for self-study by practitioners with introductory level background in statistics. It can also be used as a supplementary text in a graduate or upper level undergraduate course on reliability. I highly recommend this book to anyone interested in analysis of recurrence data.' Necip Doganaksoy, Journal of Quality Technology

Book Description

Survival data consist of a single event for each population unit, namely, end of life, which is modeled with a life distribution. However, many applications involve repeated-events data, where a unit may accumulate numerous events over time. This applied book provides practitioners with basic nonparametric methods for such data.

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