Handbook of Statistics

Advances in Survival Analysis


  • N. Balakrishnan, McMaster University, Hamilton, Canada
  • C.R. Rao, The Pennsylvania State University, PA, USA

The book covers all important topics in the area of Survival Analysis. Each topic has been covered by one or more chapters written by internationally renowned experts. Each chapter provides a comprehensive and up-to-date review of the topic. Several new illustrative examples have been used to demonstrate the methodologies developed. The book also includes an exhaustive list of important references in the area of Survival Analysis.
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Biostatisticians, Mathematical Statisticians andReliability Engineers.


Book information

  • Published: January 2004
  • Imprint: NORTH-HOLLAND
  • ISBN: 978-0-444-50079-3


"Forty papers provide an overview of survival analysis and describe the state of the art (...) in this field of statistics. " (Journal of Economic Literature, 2004-1222) "The book successfully provides the reader with an overiew of which topics are the subject of current research in survival analysis. Areas covered include (to name a few): complex patterns of information loss, bivariate survival, multi-state models, gene expression analysis, and quality of life analysis." -Jan Beyersmann, in STATISTICS IN MEDICINE, Vol. 24, 2005

Table of Contents

Preface. Contributors.

Part I. General Methodology.

Evaluation of the Performance of Survival Analysis Models: Discrimination and Calibration Measures (R.B. D'Agostino, B.-H. Nam).
Discretizing a Continuous Covariate in Survival Studies (J.P. Klein, J.-T. Wu).
On Comparison of Two Classification Methods with Survival Endpoints (Y. Lu, H. Jin, J. Mi).
Time-Varying Effects in Survival Analysis (T.H. Scheike).
Kaplan-Meier Integrals (W. Stute).

Part II. Concensored Data and Inference.

Statistical Analysis of Doubly Interval-Censored Failure Time Data (J. Sun).
The Missing Consoring-Indicator Model of Random Censorship (S. Subramanian).
Estimation of the Bivariate Survival Function with Generalized Bivariate Right Censored Data Structures (S. Keles, M.J. van der Laan, J.M. Robins).
Estimation of Semi-Markov Models with Right-Censored Data (O. Pons).

Part III. Truncated Data and Inference.

Nonparametric Bivariate Estimation with Randomly Truncated Observations (Ü. Gürler).

Part IV. Hazard Rate Estimation.

Lower Bounds for Estimating a Hazard (C. Huber, b. MacGibbon).
Non-Parametric Hazard Rate Estimation under Proressive Type-II Consoring (N. Balakrishnan, L. Bordes).

Part V. Comparison of Survival Curves.

Statistical Tests of the Equality of Survival Curves: Reconsidering the Options (G.P. Suciu, S. Lemeshow, M. Moeschberger).
Testing Equality of Survival Functions with Bivariate Censored Data: A Review (P.V. Rao).
Statistical Methods for the Comparison of Crossing Survival Curves (C.T. Le).

Part VI. Competing Risks and Analysis.

Inference for Competing Risks (J.P. Klein, R. Bajorunaite).
Analysis of Cause-Specific Events in Competing Risks Survival Data (J. Dignam, J. Bryant, H.S. Wieand).
Analysis of Progressively Censored Competing Risks Data (D. Kundu, N. Kannan, N. Balakrishnan).
Marginal Analysis of Point Processes with Competing Risks (R.J. Cook, B. Chen, P. Major).

Part VII. Propoertional Hazards Model and Analysis.

Categorical Auxiliary Data in the Discrete Time Proportional Hazards Model (P. Slasor, N. Laird).
Hosmer and Lemeshow type Goodness-of-Fit Statistics for the Cox Proportional Hazards Model (S. May, D.W. Hosmer).
The Effects of Misspecifying Cox's Regression Model on Randomized Treatment Group Comparisons (A.G. DiRienzo, S.W. Lagakos).
Statistical Modeling in Survival Analysis and Its Influence on the Duration Analysis (V. Bagdonavicius, M. Nikulin.

Part VIII. Accelerated Models and Analysis.

Accelerated Hazards Model: Method, Theory and Applications (Y.Q. Chen, N.P. Jewell, J. Yang).
Diagnostics for the Accelerated Life Time Model of Survival Data (D. Zelterman, H. Lin).
Cumulative Damage Approaches Leading to Inverse Gaussian Accelerated Test Models (A. Onar, W.J. Padgett).
On Estimating the Gamma Accelerated Failure-Time Models (K.M. Koti).

Part IX. Frailty Models and Applications.

Frailty Model and its Application to Seizure Data (N. Ebrahimi, X. Zhang, A. Berg, S. Shinnar).

Part X. Models and Applications.

State Space Models for Survival Analysis (W.Y. Tan, W. Ke).
First Hitting Time Models for Lifetime Date (M.-L.T. Lee, G.A. Whitmore).
An Increasing Hazard Cure Model (Y. Peng, K.B.G. Dear).

Part XI. Multivariate Survival Data Analysis.

Marginal Analyses of Multistage Data (G.A. Satten, S. Datta).
The Matrix-Valued Counting Process Model with Proportional Hazards for Sequential Survival Data (K.L. Kesler, P.K. Sen).

Part XII. Recurrent Event Data Analysis.

Analysis of Recurrent Event Data (J. Cai, D.E. Schaubel).

Part XIII. Current Status Data Analysis.

Current Status Data: Review, Recent Developments and Open Problems (N.P. Jewell, M. van der Laan).

Part XIV. Disease Progression Analysis.

Appraisal of Models for the Study of Disease Progression in Psoriatic Arthritis (R. Aguirre-Hernández, V.T. Farewell).

Part XV. Gene Expressions and Analysis.

Survival Analysis with Gene Expression Arrays (D.K. Pauler, J. Hardin, J.R. Faulkner, M. LeBlanc, J.J. Crowley).

Part XVI. Quality of Life Analysis.

Joint Analysis of Longitudinal Quailty of Life and Survival Processes (M. Mesbah, J.-F. Dupuy, N. Heutte, L. Awad).

Part XVII. Flowgraph Models and Applications.

Modelling Survival Data using Flowgraph Models (A.V. Huzurbazar).

Part XVIII. Repair Models and Analysis.

Nonparametric Methods for Repair Models (M. Hollander, J. Sethuraman).

Subject Index.
Contents of Previous Volumes.