Monographs on statistics and applied probability ;
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21
GENERAL NOTES
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10.6 Tests for equality of marginal distribution.
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Originally published by Chapman & Hall; first edition 1984.
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
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Includes bibliographical references and index.
CONTENTS NOTE
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Cover; Title Page; Copyright Page; Table of Contents; Preface; 1: The scope of survival analysis; 1.1 Introduction; 1.2 The definition of failure times; 1.3 Censoring; 1.4 Other methods of analysis; 1.5 Some examples; 1.6 Computing; Bibliographic notes, 1; Further results and exercises, 1; 2: Distributions of failure time; 2.1 Introduction; 2.2 Hazard function; 2.3 Some special distributions; 2.4 Comparison of distributions; Bibliographic notes, 2; Further results and exercises, 2; 3: Parametric statistical analysis: single sample; 3.1 Introduction; 3.2 The likelihood function.
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3.3 Likelihood theory: general considerations3.4 Exponentially distributed failure times; 3.5 Proportional hazards family; 3.6 Likelihood estimation for the Weibull distribution; 3.7 A test for exponentiality; Bibliographic notes, 3; Further results and exercises, 3; 4: Single-sample nonparametric methods; 4.1 Introduction; 4.2 Product-limit estimator; 4.3 Greenwood's formula; 4.4 Actuarial estimator; 4.5 Cumulative hazard estimators: goodness of fit; 4.6 Bayesian nonparametric methods; Bibliographic notes, 4; Further results and exercises, 4.
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5: Dependence on explanatory variables: model formulation5.1 Introduction; 5.2 Accelerated life model; 5.3 Proportional hazards model; 5.4 Nonmultiplicative hazard-based model; 5.5 Transferred origin model; 5.6 Accelerated onset model; 5.7 Treatments with a transient effect; 5.8 Discussion; Bibliographic notes, 5; Further results and exercises, 5; 6: Fully parametric analysis of dependency; 6.1 Introduction; 6.2 Exponential distribution; 6.3 Accelerated life model; 6.4 Proportional hazards model; 6.5 Sensitivity analysis; 6.6 Some less formal methods; Bibliographic notes, 6.
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8.7 Rank tests and the accelerated life model8.8 Sampling the risk set; 8.9 An example; Bibliographic notes, 8; Further results and exercises, 8; 9: Several types of failure; 9.1 Introduction; 9.2 Some key relations; 9.3 Statistical analysis for independent competing risks; 9.4 Proportional hazards; 9.5 Marked failures; Bibliographic notes, 9; Further results and exercises, 9; 10: Bivariate survivor functions; 10.1 Introduction; 10.2 A 'shock' model; 10.3 A continuous bivariate survival model; 10.4 Testing for independence; 10.5 Nonparametric estimation.
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Further results and exercises, 67: Proportional hazards model; 7.1 Introduction; 7.2 The likelihood function; 7.3 The derivatives of the log likelihood; 7.4 Log linear hazards; 7.5 An example; 7.6 Discrete failure times: ties; 7.7 The two-sample problem; 7.8 Estimation of baseline functions: goodness of fit; Bibliographic notes, 7; Further results and exercises, 7; 8: Time-dependent covariates; 8.1 Introduction; 8.2 Some applications of time-dependent covariates; 8.3 The likelihood function; 8.4 Partial likelihood; 8.5 Efficiency comparisons with fully parametric models; 8.6 Two-sample tests.
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SUMMARY OR ABSTRACT
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This monograph contains many ideas on the analysis of survival data to present a comprehensive account of the field. The value of survival analysis is not confined to medical statistics, where the benefit of the analysis of data on such factors as life expectancy and duration of periods of freedom from symptoms of a disease as related to a treatment applied individual histories and so on, is obvious. The techniques also find important applications in industrial life testing and a range of subjects from physics to econometrics. In the eleven chapters of the book the methods and applications of are discussed and illustrated by examples.