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Survival Analysis

Proportional and Non-Proportional Hazards Regression

  • Textbook
  • © 2021

Overview

Authors:
  1. John O'Quigley

    1. Department of Statistical Science, University College London, London WC1E 6BT, UK

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  • Summaries and exercises included in every chapter
  • Extensive appendices provided on probability, stochastic processes, and simulating data
  • Many of the advances of the last ten years, not covered elsewhere, are given prominence in this book

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Introduction

    • John O’Quigley
    Pages 1-18

  3. Survival analysis methodology

    • John O’Quigley
    Pages 19-47

  4. Survival without covariates

    • John O’Quigley
    Pages 49-73

  5. Proportional hazards models

    • John O’Quigley
    Pages 75-95

  6. Proportional hazards models in epidemiology

    • John O’Quigley
    Pages 97-118

  7. Non-proportional hazards models

    • John O’Quigley
    Pages 119-140

  8. Model-based estimating equations

    • John O’Quigley
    Pages 141-190

  9. Survival given covariate information

    • John O’Quigley
    Pages 191-213

  10. Regression effect process

    • John O’Quigley
    Pages 215-259

  11. Model construction guided by regression effect process

    • John O’Quigley
    Pages 261-299

  12. Hypothesis tests based on regression effect process

    • John O’Quigley
    Pages 301-350

  13. Back Matter

    Pages 351-475
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Keywords

About this book

This book provides an extensive coverage of the methodology of survival analysis, ranging from introductory level material to deeper more advanced topics. The framework is that of proportional and non-proportional hazards models; a structure that is broad enough to enable the recovery of a large number of established results as well as to open the way to many new developments. The emphasis is on concepts and guiding principles, logical and graphical. Formal proofs of theorems, propositions and lemmas are gathered together at the end of each chapter separate from the main presentation. 

The intended audience includes academic statisticians, biostatisticians, epidemiologists and also researchers in these fields whose focus may be more on the applications than on the theory. The text could provide the basis for a two semester course on survival analysis and, with this goal in mind, each chapter includes a section with a range of exercises as a teaching aid for instructors. 


Authors and Affiliations

  • Department of Statistical Science, University College London, London WC1E 6BT, UK

    John O'Quigley

About the author

John O’Quigley is professor of statistics in the Department of Statistical Science, University College London. Professor O'Quigley's academic career began as MRC research scientist at the University of Leeds, U.K., a stint followed by several positions in France, the most recent being in the Laboratory of Probability, Statistics and Modelling, University of Paris – Sorbonne. The most significant part of Professor O’Quigley’s career has been spent in the United States, mainly in the Department of Mathematics, University of California San Diego during which time he was a tenured full professor of mathematics. He was also Director of the Laboratory for Mathematics and Statistics. Prior to that Professor O’Quigley was a researcher at the Fred Hutchinson Cancer Research Center and the Department of Biostatistics, University of Washington, Seattle. Several years were also spent as full professor at the University of Virginia Medical School as well as the Department of Mathematics at Lancaster University, U.K.

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