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Flowgraph models for multistate time -to-event data
The main purpose of this book is to present an introduction to flowgraph models for time-to-event data. The focus is on stochastic models for censored time-to-event data with competing risks and recurrent events. The applications are geared to survival analysis and reliability. I view flowgraph models as providing a methodology for data analysis of semi-Markov processes that can be applied without becoming intimately familiar with the mathematical theory of stochastic processes. My early experience with stochastic processes left me with the impression that there were lots of nice models, but I could not think of how to analyze data with them except in the simplest cases. I found myself unhappy with the exponential assumption and limit theorems, which although they provided some approximation, did not reflect the real system. My early work in flowgraphs was on queues, but I soon found myself drawn to interesting applications in survival analysis. Consequently, I continued to work in both survival analysis and engineering systems. Flowgraphs bring together applied probability techniques such as transforms and saddlepoint methods and meld them with data analysis and statistical methods. Flowgraph models are analyzed using Bayesian methods, or if one prefers, maximum likelihood techniques. This book is intended for students and practitioners of statistics who have some background at the level of a one-year graduate course in probability and statistics. Although background in survival analysis or systems reliability is not assumed, a one-semester course or some experience with standard methods in these areas would be helpful. The first seven chapters are structured for a one-semester topics course. The remaining two chapters are more advanced. A large number of worked examples are presented along with computer code as needed. For readers who are not as interested in computation, Section 3.5 and Chapter 6 can be skipped without loss of continuity. I would like to thank the following people and institutions: Howard Snyder for my undergraduate course on aerospace systems analysis; my Ph.D. advisor, Ron Butler, who taught me about saddlepoint methods, statistics, and emphasized the importance of yoga; Richard Davis for a course on stochastic processes; my colleague, Ron Christensen, who bugged me for years to write a book on flowgraph models; Jay Kadane, who brought the project to Wiley; the series editorial board xi xii PREFACE and anonymous reviewers; the editor, Steve Quigley, and assistant editors, Susanne Steitz and Heather Bergman; and Angioline Loredo and the production staff. Portions of the work were completed in California during my sabbatical. I would like to thank my colleagues in the Statistics Group and Elvira Loredo in the Management Science Group at RAND for an unbelievably fun and collegial environment. I am grateful to Guillermo Marshall and Satish Garg for the diabetic retinopathy data; to Ira Longini for providing data from the San Francisco AIDS study; and to Kate Hall for discussions on cellular telephone network operations. The work was supported in part by the University of New Mexico. My family and friends have helped in every way possible, but primarily by putting up with me through this process, especially Jayashree and Anagha Phansalkar, Ceela McElveny and Kevin Glasgow, and Noreen Gima. For helping to maintain the general health of my mind and body, I owe thanks to my yoga teachers: Herb McDonald in Albuquerque; Gail Ackerman in Santa Fe; Claudia Kuhns in Denver; and Karen Cline and Sherry Gould in Santa Monica, who took me on as a student during my sabbatical. There are four people who helped at various stages throughout the project: ? Snehalata Huzurbazar provided much needed constructive criticism on early versions of the manuscript, early versions of S-plus saddlepoint programs, and computation for Example 3.11. ? Lillian Yau entered into many discussions and provided the retinopathy simulation of Section 8.2. ? Amit Phansalkar was always ready with a touch of humor on the all-toofrequent ?bad book days? and eager to browse portions of the manuscript. ? Finally, Brian Williams graciously accepted the fact that the first year of our marriage would involve me working on this book. In addition to painstakingly reading drafts of the manuscript, he introduced me to slice sampling and convinced me that open source software was the way to go.
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| Tan 519. 542 Huz f | PSB lt.dasar - Pascasarjana | 2 |
| Penerbit | Hobogen: John Wiley & Sons 2005 |
|---|---|
| Edisi | - |
| Subjek | - |
| ISBN/ISSN | 9780471265146 |
| Klasifikasi | NONE |
| Deskripsi Fisik | xii, 270 p. : ill. ; 26 cm. |
| Info Detail Spesifik | - |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas | Tidak Ada Data |