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Survival Analysis: State of the Art

  • Book
  • © 1992

Overview

Editors:
  1. John P. Klein

    1. Department of Statistics, The Ohio State University, Columbus, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Prem K. Goel

    1. Department of Statistics, The Ohio State University, Columbus, USA

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: NATO Science Series E: (NSSE, volume 211)

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Table of contents (27 chapters)

  1. Front Matter

    Pages i-x
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  2. Bayesian Approach to Reliability and Survival Analysis

    1. Front Matter

      Pages 1-1
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    2. Life Testing and Reliability Estimation under Asymmetric Loss

      • A. P. Basu, R. D. Thompson, Purushottam W. Laud
      Pages 3-10

    3. Bayesian Computations in Survival Models Via the Gibbs Sampler

      • Lynn Kuo, Adrian F. M. Smith, Steven MacEachern, Mike West
      Pages 11-24

    4. Bayesian Nonparametric Survival Analysis: A Comparison of the Kaplan-Meier and Berliner-Hill Estimators

      • Bruce M. Hill, Steven Maceachern
      Pages 25-46

    5. Modelling Time-Varying Hazards and Covariate Effects

      • Mike West, Mark Berliner
      Pages 47-62

  3. Bio-Medical Applications of Survival Analysis

    1. Front Matter

      Pages 63-63
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    2. Analysis of Trials with Treatment — Individual Interactions

      • Jack Cuzick, Belem Trejo, Nancy Flournoy, Peter D. Sasieni
      Pages 65-76

    3. Assessment of Dependence In the Life Times of Twins

      • Philip Hougaard, Bent Harvald, Niels V. Holm, Nancy Flournoy, M. Ataharul Islam, K. P. Singh
      Pages 77-97

    4. Estimating Random Effects In the Framingham Heart Study

      • John P. Klein, M. Moeschberger, Y. H. Li, S. T. Wang, Nancy Flournoy
      Pages 99-120

    5. Survival Analysis in Genetics: Danish Twin Data Applied To a Gerontological Question

      • James W. Vaupel, Bent Harvald, Niels V. Holm, Anatoli I. Yashin, Liang Xiu, Hari H. Dayal
      Pages 121-138

  4. Engineering Applications of Survival Analysis

    1. Front Matter

      Pages 139-139
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    2. Some Issues in the Collection and Analysis of Field Reliability Data

      • J. F. Lawless, J. D. Kalbfleisch, Saul Blumenthal
      Pages 141-152

    3. Bayesian Modeling For Fatigue Crack Curves

      • Panickos N. Palettas, Prem K. Goel, Purushottam W. Laud
      Pages 153-170

  5. Inference for Survival Models

    1. Front Matter

      Pages 171-171
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    2. Statistical Analysis Of a Weibull Process With Left- Censored Data

      • Max Engelhardt, Lee J. Bain, Saul Blumenthal
      Pages 173-195

    3. Kernel Density Estimation from Record-Breaking Data

      • S. Gulati, W. J. Padgett, Saul Blumenthal
      Pages 197-210

    4. Semiparametric Estimation Of Parametric Hazard Rates

      • Nils Lid Hjort, Mike West, Sue Leurgans
      Pages 211-236

    5. Cox-Type Regression Analysis for Large Numbers of Small Groups of Correlated Failure Time Observations

      • Eric W. Lee, L. J. Wei, David A. Amato, Sue Leurgans
      Pages 237-247

    6. Information Bounds For the Additive and Multiplicative Intensity Models

      • Peter D. Sasieni, Ian W. McKeague
      Pages 249-265
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Keywords

About this book

Survival analysis is a highly active area of research with applications spanning the physical, engineering, biological, and social sciences. In addition to statisticians and biostatisticians, researchers in this area include epidemiologists, reliability engineers, demographers and economists. The economists survival analysis by the name of duration analysis and the analysis of transition data. We attempted to bring together leading researchers, with a common interest in developing methodology in survival analysis, at the NATO Advanced Research Workshop. The research works collected in this volume are based on the presentations at the Workshop. Analysis of survival experiments is complicated by issues of censoring, where only partial observation of an individual's life length is available and left truncation, where individuals enter the study group if their life lengths exceed a given threshold time. Application of the theory of counting processes to survival analysis, as developed by the Scandinavian School, has allowed for substantial advances in the procedures for analyzing such experiments. The increased use of computer intensive solutions to inference problems in survival analysis~ in both the classical and Bayesian settings, is also evident throughout the volume. Several areas of research have received special attention in the volume.

Editors and Affiliations

  • Department of Statistics, The Ohio State University, Columbus, USA

    John P. Klein, Prem K. Goel

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