Bayesian Survival Analysis

Name: Bayesian Survival Analysis
Price: 46.36 USD
Availability: InStock
ISBN: 9780387952772

ISBN-10: 0387952772

ISBN-13: 9780387952772

Edition: 2001

Authors: Joseph G. Ibrahim, Ming-Hui Chen, Debajyoti Sinha

List price: $219.99

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Description:

Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. Several topics are addressed, including parametric models, semiparametric models based on prior processes, proportional and non-proportional hazards models, frailty models, cure rate models, model selection and comparison, joint models for longitudinal and survival data, models with time varying covariates, missing covariate data, design and monitoring of clinical trials, accelerated failure time models, models for multivariate survival data, and special types of hierarchical…

Book details

List price: $219.99
Copyright year: 2001
Publisher: Springer New York
Publication date: 6/26/2001
Binding: Hardcover
Pages: 481
Size: 6.10" wide x 9.25" long x 1.00" tall
Weight: 1.980
Language: English



Preface



Introduction



Aims



Outline



Motivating Examples



Survival Analysis



Proportional Hazards Models



Censoring



Partial Likelihood



The Bayesian Paradigm



Sampling from the Posterior Distribution



Informative Prior Elicitation



Why Bayes?


Exercises



Parametric Models



Exponential Model



Weibull Model



Extreme Value Model



Log-Normal Model



Gamma Model


Exercises



Semiparametric Models



Piecewise Constant Hazard Model



Models Using a Gamma Process



Gamma Process on Cumulative Hazard



Gamma Process with Grouped-Data Likelihood



Relationship to Partial Likelihood



Gamma Process on Baseline Hazard



Prior Elicitation



Approximation of the Prior



Choices of Hyperparameters



Sampling from the Joint Posterior Distribution of ([beta], [delta], a[subscript 0])



A Generalization of the Cox Model



Beta Process Models



Beta Process Priors



Interval Censored Data



Correlated Gamma Processes



Dirichlet Process Models



Dirichlet Process Prior



Dirichlet Process in Survival Analysis



Dirichlet Process with Doubly Censored Data



Mixtures of Dirichlet Process Models



Conjugate MDP Models



Nonconjugate MDP Models



MDP Priors with Censored Data



Inclusion of Covariates


Exercises



Frailty Models



Proportional Hazards Model with Frailty



Weibull Model with Gamma Frailties



Gamma Process Prior for H[subscript 0](t)



Piecewise Exponential Model for h[subscript 0](t)



Positive Stable Frailties



A Bayesian Model for Institutional Effects



Posterior Likelihood Methods



Methods Based on Partial Likelihood



Multiple Event and Panel Count Data



Multilevel Multivariate Survival Data



Bivariate Measures of Dependence


Exercises



Cure Rate Models



Introduction



Parametric Cure Rate Model



Models



Prior and Posterior Distributions



Posterior Computation



Semiparametric Cure Rate Model



An Alternative Semiparametric Cure Rate Model



Prior Distributions



Multivariate Cure Rate Models



Models



The Likelihood Function



The Prior and Posterior Distributions



Computational Implementation


Appendix


Exercises



Model Comparison



Posterior Model Probabilities



Variable Selection in the Cox Model



Prior Distribution on the Model Space



Computing Prior and Posterior Model Probabilities



Criterion-Based Methods



The L Measure



The Calibration Distribution



Conditional Predictive Ordinate



Bayesian Model Averaging



BMA for Variable Selection in the Cox Model



Identifying the Models in A'



Assessment of Predictive Performance



Bayesian Information Criterion



Model Selection Using BIC



Exponential Survival Model



The Cox Proportional Hazards Model


Exercises



Joint Models for Longitudinal and Survival Data



Introduction



Joint Modeling in AIDS Studies



Joint Modeling in Cancer Vaccine Trials



Joint Modeling in Health-Related Quality of Life Studies



Methods for Joint Modeling of Longitudinal and Survival Data



Partial Likelihood Models



Joint Likelihood Models



Mixture Models



Bayesian Methods for Joint Modeling of Longitudinal and Survival Data


Exercises



Missing Covariate Data



Introduction



The Cure Rate Model with Missing Covariate Data



A General Class of Covariate Models



The Prior and Posterior Distributions



Model Checking


Appendix


Exercises



Design and Monitoring of Randomized Clinical Trials



Group Sequential Log-Rank Tests for Survival Data



Bayesian Approaches



Range of Equivalence



Prior Elicitation



Predictions



Checking Prior-Data Compatibility



Bayesian Sample Size Determination



Alternative Approaches to Sample Size Determination


Exercises



Other Topics



Proportional Hazards Models Built from Monotone Functions



Likelihood Specification



Prior Specification



Time-Dependent Covariates



Accelerated Failure Time models



MDP Prior for [theta subscript i]



Polya Tree Prior for [theta subscript i]



Bayesian Survival Analysis Using MARS



The Bayesian Model



Survival Analysis with Frailties



Change Point Models



Basic Assumptions and Model



Extra Poisson Variation



Lag Functions



Recurrent Tumors



Bayesian Inference



The Poly-Weibull Model



Likelihood and Priors



Sampling the Posterior Distribution



Flexible Hierarchical Survival Models



Three Stages of the Hierarchical Model



Implementation



Bayesian Model Diagnostics



Bayesian Latent Residuals



Prequential Methods



Future Research Topics


Appendix


Exercises


List of Distributions


References


Author Index


Subject Index