Advanced Survival Models (Chapman & Hall/CRC Biostatistics Series)

Cover\nHalf Title\nSeries Page\nTitle Page\nCopyright Page\nDedication\nContents\nPreface\nAcknowledgment for use of data\nList of Figures\nList of Tables\nAuthor\nSymbols\n1. Introduction\n	1.1. Survival data analysis\n	1.2. Basic concepts\n		1.2.1. Censoring and truncation\n		1.2.2. Basic functions\n	1.3. Examples\n		1.3.1. Colon cancer data\n		1.3.2. Rectal cancer data\n		1.3.3. Diabetic retinopathy data\n		1.3.4. Children ALL data\n		1.3.5. Melanoma data\n		1.3.6. Advanced ovarian cancer data\n	1.4. Scope of this book\n2. Classical Survival Analysis\n	2.1. Introduction\n	2.2. Likelihood function\n	2.3. Estimation of the survival and hazard function\n		2.3.1. Parametric estimation\n		2.3.2. Non-parametric estimation\n	2.4. Hypothesis testing\n	2.5. Modeling survival data\n		2.5.1. Proportional hazards models\n		2.5.2. Accelerated failure time models\n		2.5.3. Proportional odds models\n	2.6. Software and examples revisited\n		2.6.1. Available softwares for classical survival analysis\n		2.6.2. Colon cancer data\n		2.6.3. Rectal cancer data\n	2.7. Further reading\n3. Frailty Models\n	3.1. Introduction\n	3.2. Univariate frailty models\n	3.3. Multivariate frailty models\n	3.4. Frailty distributions\n		3.4.1. Discrete frailty distribution\n		3.4.2. Continuous frailty distribution\n	3.5. Estimation\n		3.5.1. Parametric frailty models\n		3.5.2. Semi-parametric frailty models\n	3.6. Extensions of the shared frailty model\n	3.7. Software and examples revisited\n		3.7.1. Diabetic retinopathy data\n		3.7.2. Rectal cancer data\n	3.8. Further reading\n4. Cure Models\n	4.1. Introduction\n	4.2. Mixture cure models\n		4.2.1. The incidence and the latency submodels\n		4.2.2. Estimation\n		4.2.3. Interpretation\n	4.3. Promotion time cure models\n		4.3.1. Estimation\n		4.3.2. Interpretation\n		4.3.3. Extended promotion time cure model\n	4.4. When to use a cure model\n	4.5. Software and examples revisited\n		4.5.1. Children ALL data\n		4.5.2. Melanoma data\n	4.6. Further reading\n5. Competing Risks\n	5.1. Introduction\n	5.2. Basic concepts, notations, and definitions\n		5.2.1. Combined analysis or time to the first event analysis\n		5.2.2. Marginal analysis\n		5.2.3. Competing risk analysis\n		5.2.4. A note on censoring\n	5.3. Estimation\n	5.4. Hypotheses testing\n	5.5. Modeling\n		5.5.1. Proportional cause-specific hazards model\n		5.5.2. Fine and Gray model\n		5.5.3. Choice of model\n	5.6. Software and examples revisited\n		5.6.1. Advanced ovarian cancer data\n	5.7. Further reading\n6. Joint Modeling\n	6.1. Introduction\n	6.2. Time-dependent covariates in survival models\n		6.2.1. Exogenous time-dependent covariates and extended Cox model\n		6.2.2. Endogenous time-dependent covariates and joint models\n	6.3. The shared random effect approach\n		6.3.1. Model for the marker trajectory\n		6.3.2. Model for the time-to-event outcome\n		6.3.3. Estimation\n		6.3.4. Association structure\n	6.4. The joint latent class approach\n		6.4.1. Model for the latent class membership probability\n		6.4.2. Model for the class-specific marker trajectory\n		6.4.3. Model for the class-specific risk of event\n		6.4.4. Estimation\n	6.5. JCLM versus SREM\n	6.6. Software\n	6.7. Further reading\nBibliography\nIndex