The statistical analysis of multivariate time data : a marginal modeling approach /: a marginal modeling approach. (2019)

• Record Type: Book
• Further Information: Note: Ross L. Prentice, Shanshan Zhao.
• Authors: Prentice, Ross L; Zhao, Shanshan, 1983-
• Contents: 1. Introduction and Characterization of Multivariate Failure Time Distributions Failure Time Data and Distributions Bivariate Failure Time Data and Distributions Bivariate Failure Time Regression Modeling Higher Dimensional Failure Time Data and Distributions Multivariate Response Data: Modeling and Analysis Recurrent Event Characterization and Modeling Some Application Settings Aplastic anemia clinical trial Australian twin data Women’s Health Initiative hormone therapy trials Bladder tumor recurrence data Women’s Health Initiative dietary modification trial 2. Univariate Failure Time Data Analysis Methods Overview Nonparametric Survivor Function Estimation Hazard Ratio Regression Estimation Using the Cox Model Cox Model Properties and Generalizations Censored Data Rank Tests Cohort Sampling and Dependent Censoring Aplastic Anemia Clinical Trial Application WHI Postmenopausal Hormone Therapy Application Asymptotic Distribution Theory Additional Univariate Failure Time Models and Methods Cox-Logistic Model for Failure Time Data 3. Nonparametric Estimation of the Bivariate Survivor Function Introduction Plug-In Nonparametric Estimators of F The Volterra estimator The Dabrowska and Prentice–Cai estimators Simulation evaluation Asymptotic distributional results Maximum Likelihood and Estimating Equation Approaches Nonparametric Assessment of Dependency Cross ratio and concordance function estimators Australian twin study illustration Simulation evaluation Additional Estimators and Estimation Perspectives Additional bivariate survivor function estimators Estimation perspectives 4. Regression Analysis of Bivariate Failure Time Data Introduction Independent Censoring and Likelihood-Based Inference Copula Models and Estimation Methods Formulation Likelihood-based estimation Unbiased estimating equations Frailty Models and Estimation Methods Australian Twin Study Illustration Hazard Rate Regression Semiparametric regression model possibilities Cox models for marginal single and dual outcome hazard rates Dependency measures given covariates Asymptotic distribution theory Simulation evaluation of marginal hazard rate estimators Composite Outcomes in a Low-Fat Diet Trial Counting Process Intensity Modeling Marginal Hazard Rate Regression in Context Likelihood maximization and empirical plug-in estimators Independent censoring and death outcomes Marginal hazard rates for competing risk data Summary 5. Trivariate Failure Time Data Modeling and Analysis Introduction Trivariate Survivor Function Estimation Dabrowska-type Estimator Development Volterra Estimator Trivariate Dependency Assessment Simulation Evaluation and Comparison Trivariate Regression Analysis via Copulas Marginal Hazard Rate Regression Simulation Evaluation of Hazard Ratio Estimators Hormone Therapy and Disease Occurrence 6. Higher Dimensional Failure Time Data Modeling and Estimation Introduction M-dimensional Survivor Function Estimation Dabrowska-type estimator development Volterra nonparametric survivor function estimator Multivariate dependency assessment Single Failure Hazard Rate Regression Regression on Marginal Hazard Rates and Dependencies Likelihood specification Estimation using copula models Marginal Single and Double Failure Hazard Rate Modeling Counting Process Intensity Modeling and Estimation Women’s Health Initiative Hormone Therapy Illustration More on Estimating Equations and Likelihood 7. Recurrent Event Data Analysis Methods Introduction Intensity Process Modeling on a Single Failure Time Axis Counting process intensity modeling and estimation Bladder tumor recurrence illustration Intensity modeling with multiple failure types Marginal Failure Rate Estimation with Recurrent Events Single and Double Failure Rate Models for Recurrent Events WHI Dietary Modification Trial Illustration Absolute Failure Rates and Mean Models for Recurrent Events Intensity Versus Marginal Hazard Rate Modeling 8. Additional Important Multivariate Failure Time Topics Introduction Dependent Censorship, Confounding and Mediation Dependent censorship Confounding control and mediation analysis Cohort Sampling and Missing Covariates Introduction Case-cohort and two-phase sampling Nested case–control sampling Missing covariate data methods Mismeasured Covariate Data Background Hazard rate estimation with a validation subsample Hazard rate estimation without a validation subsample Energy intake and physical activity in relation to chronic disease risk Joint Covariate and Failure Rate Modeling Model Checking Marked Point Processes and Multistate Models Imprecisely Measured Failure Times Appendix : Technical Materials A Product Integrals and Steiltjes Integration A Generalized Estimating Equations for Mean Parameters A Some Basic Empirical Process Results Appendix Software and Data A Software for Multivariate Failure Time Analysis A Data Access
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2019
• Extent: 1 online resource
• Subjects: 519.535; Failure time data analysis; Multivariate analysis
• Languages: English
• ISBNs: 9780429529702; 9781482256581; 9780429544408; 9780429162367
• Related ISBNs: 9781482256574
• Notes: Note: Includes bibliographical references.; Note: Description based on CIP data; resource not viewed.
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