Skip to main content
SpringerLink
Log in

Statistical Models Based on Counting Processes

  • Textbook
  • © 1993

Overview

Authors:
  1. Per Kragh Andersen

    1. Statistical Research Unit, University of Copenhagen, Copenhagen, Denmark

    View author publications

    You can also search for this author in PubMed   Google Scholar

  2. Ørnulf Borgan

    1. Institute of Mathematics, University of Oslo, Oslo, Norway

    View author publications

    You can also search for this author in PubMed   Google Scholar

  3. Richard D. Gill

    1. Faculty of Mathematics, University of Utrecht, Utrecht, The Netherlands

    View author publications

    You can also search for this author in PubMed   Google Scholar

  4. Niels Keiding

    1. Statistical Research Unit, University of Copenhagen, Copenhagen, Denmark

    View author publications

    You can also search for this author in PubMed   Google Scholar

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

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 139.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (10 chapters)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Introduction

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 1-44

  3. The Mathematical Background

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 45-120

  4. Model Specification and Censoring

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 121-175

  5. Nonparametric Estimation

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 176-331

  6. Nonparametric Hypothesis Testing

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 332-400

  7. Parametric Models

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 401-475

  8. Regression Models

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 476-591

  9. Asymptotic Efficiency

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 592-659

  10. Frailty Models

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 660-674

  11. Multivariate Time Scales

    • Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding
    Pages 675-708

  12. Back Matter

    Pages 709-768
    Download chapter PDF
Back to top

Keywords

About this book

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

Reviews

"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

Authors and Affiliations

  • Statistical Research Unit, University of Copenhagen, Copenhagen, Denmark

    Per Kragh Andersen, Niels Keiding

  • Institute of Mathematics, University of Oslo, Oslo, Norway

    Ørnulf Borgan

  • Faculty of Mathematics, University of Utrecht, Utrecht, The Netherlands

    Richard D. Gill

Bibliographic Information

  • Book Title: Statistical Models Based on Counting Processes

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

  • Series Title: Springer Series in Statistics

  • DOI: https://doi.org/10.1007/978-1-4612-4348-9

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag New York, Inc. 1993

  • Softcover ISBN: 978-0-387-94519-4Published: 23 June 1995

  • eBook ISBN: 978-1-4612-4348-9Published: 06 December 2012

  • Series ISSN: 0172-7397

  • Series E-ISSN: 2197-568X

  • Edition Number: 1

  • Number of Pages: XI, 784

  • Topics: Statistical Theory and Methods

Publish with us

Policies and ethics

Back to top

Search

Navigation