Flowgraph Models for Multistate Time-to-Event Data

Flowgraph Models for Multistate Time-to-Event Data
Author :
Publisher : John Wiley & Sons
Total Pages : 320
Release :
ISBN-10 : 9780471686538
ISBN-13 : 0471686530
Rating : 4/5 (38 Downloads)

Book Synopsis Flowgraph Models for Multistate Time-to-Event Data by : Aparna V. Huzurbazar

Download or read book Flowgraph Models for Multistate Time-to-Event Data written by Aparna V. Huzurbazar and published by John Wiley & Sons. This book was released on 2004-12-03 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique introduction to the innovative methodology of statisticalflowgraphs This book offers a practical, application-based approach toflowgraph models for time-to-event data. It clearly shows how thisinnovative new methodology can be used to analyze data fromsemi-Markov processes without prior knowledge of stochasticprocesses--opening the door to interesting applications in survivalanalysis and reliability as well as stochastic processes. Unlike other books on multistate time-to-event data, this workemphasizes reliability and not just biostatistics, illustratingeach method with medical and engineering examples. It demonstrateshow flowgraphs bring together applied probability techniques andcombine them with data analysis and statistical methods to answerquestions of practical interest. Bayesian methods of data analysisare emphasized. Coverage includes: * Clear instructions on how to model multistate time-to-event datausing flowgraph models * An emphasis on computation, real data, and Bayesian methods forproblem solving * Real-world examples for analyzing data from stochasticprocesses * The use of flowgraph models to analyze complex stochasticnetworks * Exercise sets to reinforce the practical approach of thisvolume Flowgraph Models for Multistate Time-to-Event Data is an invaluableresource/reference for researchers in biostatistics/survivalanalysis, systems engineering, and in fields that use stochasticprocesses, including anthropology, biology, psychology, computerscience, and engineering.


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