Statistical Models Based on Counting Processes

  • Per Kragh Andersen
  • Ørnulf Borgan
  • Richard D. Gill
  • Niels Keiding

Part of the Springer Series in Statistics book series (SSS)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 1-44
  3. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 45-120
  4. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 121-175
  5. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 176-331
  6. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 332-400
  7. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 401-475
  8. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 476-591
  9. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 592-659
  10. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 660-674
  11. Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 675-708
  12. Back Matter
    Pages 709-768

About this book

Introduction

Modern survival analysis and more general event history analysis may be effectively handled in the mathematical framework of counting processes, stochastic integration, martingale central limit theory and product integration. This book presents this theory, which has been the subject of an intense research activity during the past one-and-a- half decades. The exposition of the theory is integrated with careful presentation of many practical examples, almost exclusively from the authors' own experience, with detailed numerical and graphical illustrations. Statistical Models Based on Counting Processes may be viewed as a research monograph for mathematical statisticians and biostatisticians, although almost all methods are given in concrete detail to be used in practice by other mathematically oriented researchers studying event histories (demographers, econometricians, epidemiologists, actuarial mathematicians, reliabilty engineers and biologists). Much of the material has so far only been available in the journal literature (if at all), and so a wide variety of researchers will find this an invaluable survey of the subject.
"This book is a masterful account of the counting process approach...is certain to be the standard reference for the area, and should be on the bookshelf of anyone interested in event-history analysis." International Statistical Institute Short Book Reviews "...this impressive reference, which contains a a wealth of powerful mathematics, practical examples, and analytic insights, as well as a complete integration of historical developments and recent advances in event history analysis." Journal of the American Statistical Association

Keywords

censoring estimator likelihood survival analysis

Authors and affiliations

  • Per Kragh Andersen
    • 1
  • Ørnulf Borgan
    • 2
  • Richard D. Gill
    • 3
  • Niels Keiding
    • 1
  1. 1.Statistical Research UnitUniversity of CopenhagenCopenhagenDenmark
  2. 2.Institute of MathematicsUniversity of OsloOsloNorway
  3. 3.Faculty of MathematicsUniversity of UtrechtUtrechtThe Netherlands

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-4348-9
  • Copyright Information Springer-Verlag New York 1993
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-94519-4
  • Online ISBN 978-1-4612-4348-9
  • Series Print ISSN 0172-7397
  • About this book