Preface |
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vii | |
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1 | (14) |
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1 | (1) |
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A Data Set and Some Examples |
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2 | (13) |
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The Counting Process and Martingale Framework |
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15 | (36) |
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15 | (1) |
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Stochastic Processes and Stochastic Integrals |
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15 | (10) |
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25 | (6) |
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The Doob-Meyer Decomposition: Applications to Quadratic Variation |
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31 | (11) |
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The Martingale Transform ∫HdM |
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42 | (6) |
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48 | (3) |
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Local Square Integrable Martingales |
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51 | (38) |
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51 | (1) |
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Localization of Stochastic Processes and the Doob-Meyer Decomposition |
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52 | (8) |
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The Martingale N - A Revisited |
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60 | (5) |
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Stochastic Integrals with Respect to Local Martingales |
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65 | (9) |
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74 | (5) |
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Compensators with Discontinuities |
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79 | (4) |
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83 | (5) |
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88 | (1) |
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Finite Sample Moments and Large Sample Consistency of Tests and Estimators |
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89 | (36) |
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89 | (2) |
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Nonparametric Estimation of the Survival Distribution |
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91 | (16) |
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Some Finite Sample Properties of Linear Rank Statistics |
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107 | (5) |
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Consistency of the Kaplan-Meier Estimator |
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112 | (9) |
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121 | (4) |
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Censored Data Regression Models and Their Application |
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125 | (76) |
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125 | (1) |
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The Proportional Hazards and Multiplicative Intensity Models |
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126 | (10) |
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Partial Likelihood Inference |
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136 | (17) |
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Applications of Partial Likelihood Methods |
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153 | (10) |
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163 | (15) |
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Applications of Residual Methods |
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178 | (19) |
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197 | (4) |
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Martingale Central Limit Theorem |
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201 | (28) |
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Preliminaries and Motivation |
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201 | (4) |
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Convergence of Martingale Difference Arrays |
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205 | (10) |
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Weak Convergence of the Process, U(n) |
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215 | (13) |
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228 | (1) |
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Large Sample Results of the Kaplan-Meier Estimator |
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229 | (26) |
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229 | (1) |
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A Large Sample Result for Kaplan-Meier and Weighted Logrank Statistics |
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229 | (6) |
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Confidence Bands for the Survival Distribution |
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235 | (17) |
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252 | (3) |
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Weighted Logrank Statistics |
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255 | (32) |
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255 | (1) |
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Large Sample Null Distribution |
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256 | (9) |
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Consistency of Tests of the Class K |
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265 | (2) |
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Efficiencies of Tests of the Class K |
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267 | (10) |
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Some Versatile Test Procedures |
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277 | (7) |
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284 | (3) |
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Distribution Theory for Proportional Hazards Regression |
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287 | (30) |
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287 | (2) |
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The Partial Likelihood Score Statistic |
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289 | (7) |
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Estimators of the Regression Parameters and the Cumulative Hazard Function |
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296 | (7) |
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The Asymptotic Theory for Simple Models |
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303 | (8) |
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Asymptotic Relative Efficiency of Partial Likelihood Inference in the Proportional Hazards Model |
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311 | (5) |
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316 | (1) |
Appendix A. Some Results from Stieltjes Integration and Probability Theory |
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317 | (14) |
Appendix B. An Introduction to Weak Convergence |
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331 | (12) |
Appendix C. The Martingale Central Limit Theorem: Some Preliminaries |
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343 | (16) |
Appendix D. Data |
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359 | (26) |
Appendix E. Exercises |
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385 | (16) |
Bibliography |
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401 | (12) |
Notation |
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413 | (4) |
Author Index |
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417 | (4) |
Subject Index |
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421 | |