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The Resource Statistical analysis with measurement error or misclassification : strategy, method and application, Grace Y. Yi, (electronic book)

Statistical analysis with measurement error or misclassification : strategy, method and application, Grace Y. Yi, (electronic book)

Label
Statistical analysis with measurement error or misclassification : strategy, method and application
Title
Statistical analysis with measurement error or misclassification
Title remainder
strategy, method and application
Statement of responsibility
Grace Y. Yi
Creator
Subject
Language
eng
Member of
Cataloging source
YDX
http://library.link/vocab/creatorName
Yi, Grace Y
Dewey number
511/.43
Index
index present
LC call number
QA275
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Springer series in statistics
http://library.link/vocab/subjectName
  • Errors-in-variables models
  • Error analysis (Mathematics)
Label
Statistical analysis with measurement error or misclassification : strategy, method and application, Grace Y. Yi, (electronic book)
Instantiates
Publication
Bibliography note
Includes bibliographical references and indexes
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
Dimensions
unknown
Extent
1 online resource.
Form of item
online
Isbn
9781493966387
Specific material designation
remote
Label
Statistical analysis with measurement error or misclassification : strategy, method and application, Grace Y. Yi, (electronic book)
Publication
Bibliography note
Includes bibliographical references and indexes
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
Dimensions
unknown
Extent
1 online resource.
Form of item
online
Isbn
9781493966387
Specific material designation
remote

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