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Table of Contents
Preface; About the Author; Contents; 1 Inference Framework and Method ; 1.1 Framework and Objective; 1.2 Modeling and Estimator; 1.2.1 Parameter and Identifiability; 1.2.2 Parameter Estimator; 1.2.3 Concepts in Asymptotic Sense; 1.3 Estimation Methods; 1.3.1 Likelihood Method; 1.3.2 Estimating Equations; 1.3.3 Generalized Method of Moments; 1.3.4 Profiling Method; 1.4 Model Misspecification; 1.5 Covariates and Regression Models; 1.6 Bibliographic Notes and Discussion; 1.7 Supplementary Problems; 2 Measurement Error and Misclassification: Introduction
2.1 Measurement Error and Misclassification2.2 An Illustration of Measurement Error Effects; 2.3 The Scope of Analysis with Mismeasured Data; 2.4 Issues in the Presence of Measurement Error; 2.5 General Strategy of Handling Measurement Error ; 2.5.1 Likelihood-Based Correction Methods; 2.5.2 Unbiased Estimating Functions Methods; 2.5.3 Methods of Correcting Naive Estimators; 2.5.4 Discussion; 2.6 Measurement Error and Misclassification Models; 2.7 Measurement Error and Misclassification Examples; 2.7.1 Survival Data Example: Busselton Health Study; 2.7.2 Recurrent Event Example: rhDNase Data
2.7.3 Longitudinal Data Example: Framingham HeartStudy2.7.4 Multi-State Model Example: HL Data; 2.7.5 Case-Control Study Example: HSV Data; 2.8 Bibliographic Notes and Discussion; 2.9 Supplementary Problems; 3 Survival Data with Measurement Error; 3.1 Framework of Survival Analysis: Models and Methods; 3.1.1 Basic Measures; 3.1.2 Some Parametric Modeling Strategies; 3.1.3 Regression Models; 3.1.4 Special Features of Survival Data; 3.1.5 Likelihood Method; 3.1.6 Model-Dependent Inference Methods; 3.2 Measurement Error Effects and Inference Framework; 3.2.1 Induced Hazard Function
3.2.2 Discussion and Assumptions3.3 Approximate Methods for Measurement Error Correction; 3.3.1 Regression Calibration Method; 3.3.2 Simulation Extrapolation Method; 3.4 Methods Based on the Induced Hazard Function; 3.4.1 Induced Likelihood Method; 3.4.2 Induced Partial Likelihood Method; 3.5 Likelihood-Based Methods; 3.5.1 Insertion Correction: Piecewise-Constant Method; 3.5.2 Expectation Correction: Two-Stage Method; 3.6 Methods Based on Estimating Functions; 3.6.1 Proportional Hazards Model; 3.6.2 Simulation Study; 3.6.3 Additive Hazards Model; 3.6.4 An Example: Analysis of ACTG175 Data
3.7 Misclassification of Discrete Covariates3.7.1 Methods with Known Misclassification Probabilities; 3.7.2 Method with a Validation Sample; 3.7.3 Method with Replicates; 3.8 Multivariate Survival Data with Covariate MeasurementError; 3.8.1 Marginal Approach; 3.8.2 Dependence Parameter Estimation of Copula Models; 3.8.3 EM Algorithm with Frailty Measurement ErrorModel; 3.9 Bibliographic Notes and Discussion; 3.10 Supplementary Problems; 4 Recurrent Event Data with Measurement Error ; 4.1 Analysis Framework for Recurrent Events; 4.1.1 Notation and Framework
2.1 Measurement Error and Misclassification2.2 An Illustration of Measurement Error Effects; 2.3 The Scope of Analysis with Mismeasured Data; 2.4 Issues in the Presence of Measurement Error; 2.5 General Strategy of Handling Measurement Error ; 2.5.1 Likelihood-Based Correction Methods; 2.5.2 Unbiased Estimating Functions Methods; 2.5.3 Methods of Correcting Naive Estimators; 2.5.4 Discussion; 2.6 Measurement Error and Misclassification Models; 2.7 Measurement Error and Misclassification Examples; 2.7.1 Survival Data Example: Busselton Health Study; 2.7.2 Recurrent Event Example: rhDNase Data
2.7.3 Longitudinal Data Example: Framingham HeartStudy2.7.4 Multi-State Model Example: HL Data; 2.7.5 Case-Control Study Example: HSV Data; 2.8 Bibliographic Notes and Discussion; 2.9 Supplementary Problems; 3 Survival Data with Measurement Error; 3.1 Framework of Survival Analysis: Models and Methods; 3.1.1 Basic Measures; 3.1.2 Some Parametric Modeling Strategies; 3.1.3 Regression Models; 3.1.4 Special Features of Survival Data; 3.1.5 Likelihood Method; 3.1.6 Model-Dependent Inference Methods; 3.2 Measurement Error Effects and Inference Framework; 3.2.1 Induced Hazard Function
3.2.2 Discussion and Assumptions3.3 Approximate Methods for Measurement Error Correction; 3.3.1 Regression Calibration Method; 3.3.2 Simulation Extrapolation Method; 3.4 Methods Based on the Induced Hazard Function; 3.4.1 Induced Likelihood Method; 3.4.2 Induced Partial Likelihood Method; 3.5 Likelihood-Based Methods; 3.5.1 Insertion Correction: Piecewise-Constant Method; 3.5.2 Expectation Correction: Two-Stage Method; 3.6 Methods Based on Estimating Functions; 3.6.1 Proportional Hazards Model; 3.6.2 Simulation Study; 3.6.3 Additive Hazards Model; 3.6.4 An Example: Analysis of ACTG175 Data
3.7 Misclassification of Discrete Covariates3.7.1 Methods with Known Misclassification Probabilities; 3.7.2 Method with a Validation Sample; 3.7.3 Method with Replicates; 3.8 Multivariate Survival Data with Covariate MeasurementError; 3.8.1 Marginal Approach; 3.8.2 Dependence Parameter Estimation of Copula Models; 3.8.3 EM Algorithm with Frailty Measurement ErrorModel; 3.9 Bibliographic Notes and Discussion; 3.10 Supplementary Problems; 4 Recurrent Event Data with Measurement Error ; 4.1 Analysis Framework for Recurrent Events; 4.1.1 Notation and Framework