Flowgraph Models for Multistate Time-to-Event Data

A unique introduction to the innovative methodology of statistical
flowgraphs

This book offers a practical, application-based approach to
flowgraph models for time-to-event data. It clearly shows how this
innovative new methodology can be used to analyze data from
semi-Markov processes without prior knowledge of stochastic
processes--opening the door to interesting applications in survival
analysis and reliability as well as stochastic processes.

Unlike other books on multistate time-to-event data, this work
emphasizes reliability and not just biostatistics, illustrating
each method with medical and engineering examples. It demonstrates
how flowgraphs bring together applied probability techniques and
combine them with data analysis and statistical methods to answer
questions of practical interest. Bayesian methods of data analysis
are emphasized. Coverage includes:

* Clear instructions on how to model multistate time-to-event data
using flowgraph models

* An emphasis on computation, real data, and Bayesian methods for
problem solving

* Real-world examples for analyzing data from stochastic
processes

* The use of flowgraph models to analyze complex stochastic
networks

* Exercise sets to reinforce the practical approach of this
volume

Flowgraph Models for Multistate Time-to-Event Data is an invaluable
resource/reference for researchers in biostatistics/survival
analysis, systems engineering, and in fields that use stochastic
processes, including anthropology, biology, psychology, computer
science, and engineering.