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Measuring Agreement : Models, Methods, and Applications.

By: Contributor(s): Material type: TextTextSeries: Wiley Series in Probability and Statistics SeriesPublisher: Newark : John Wiley & Sons, Incorporated, 2017Copyright date: ©2017Edition: 1st edDescription: 1 online resource (357 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118553145
Subject(s): Genre/Form: Additional physical formats: Print version:: Measuring AgreementLOC classification:
  • QA276.A2.C468 2017
Online resources:
Contents:
Intro -- MEASURING AGREEMENT -- Contents -- Preface -- 1 Introduction -- 1.1 Preview -- 1.2 Notational Conventions -- 1.3 Basic Characteristics of a Measurement Method -- 1.3.1 A Statistical Model for Measurements -- 1.3.2 Quality Characteristics -- 1.4 Method Comparison Studies -- 1.5 Meaning of Agreement -- 1.6 A Measurement Error Model -- 1.6.1 Identifiability Issues -- 1.6.2 Model-Based Moments -- 1.6.3 Conditions for Perfect Agreement -- 1.6.4 Link to Test Theory -- 1.7 Similarity versus Agreement -- 1.7.1 Evaluation of Similarity -- 1.7.2 Evaluation of Agreement -- 1.8 A Toy Example -- 1.9 Controversies and Our View -- 1.10 Concepts Related to Agreement -- 1.11 Role of Confidence Intervals and Hypotheses Testing -- 1.11.1 Formulating the Agreement Hypotheses -- 1.11.2 Testing Hypotheses Using Confidence Bounds -- 1.11.3 Evaluation of Agreement Using Confidence Bounds -- 1.11.4 Evaluation of Similarity Using Confidence Intervals -- 1.12 Common Models for Paired Measurements Data -- 1.12.1 A Measurement Error Model -- 1.12.2 A MixedEffects Model -- 1.12.3 A Bivariate Normal Model -- 1.12.4 Limitations of the Paired Measurements Design -- 1.13 The Bland-Altman Plot -- 1.13.1 The Ideal Plot -- 1.13.2 A Linear Trend in the Bland-Altman Plot -- 1.13.3 Heteroscedasticity in the Bland-Altman Plot -- 1.13.4 Variations of the Bland-Altman Plot -- 1.14 Common Regression Approaches -- 1.14.1 Ordinary Linear Regression -- 1.14.2 Deming Regression -- 1.15 Inappropriate Use of Common Tests in Method Comparison Studies -- 1.15.1 Test of Zero Correlation -- 1.15.2 Paired t-test -- 1.15.3 Piviitman-Morgan and Bradley-Blackwood Tests -- 1.15.4 Test of Zero Intercept and Unit Slope -- 1.16 Key Steps in the Analysis of Method Comparison Data -- 1.17 Chapter Summary -- 1.18 Bibliographic Note -- Exercises -- 2 Common Approaches for Measuring Agreement.
2.1 Preview -- 2.2 Introduction -- 2.3 Mean Squared Deviation -- 2.4 Concordance Correlation Coefficient -- 2.5 A Digression: Tolerance and Prediction intervals -- 2.5.1 Definitions -- 2.5.2 Normally Distributed Data -- 2.6 Lin's Probability Criterion and Bland-Altman Criterion -- 2.7 Limits of Agreement -- 2.7.1 The Approach -- 2.7.2 Why Ignore the Variability? -- 2.7.3 Limits of Agreement versus Prediction and Tolerance Intervals -- 2.8 Total Deviation Index and Coverage Probability -- 2.8.1 The Approaches -- 2.8.2 Normally Distributed Differences -- 2.9 Inference on Agreement Measures -- 2.10 Chapter Summary -- 2.11 Bibliographic Note -- Exercises -- 3 A General Approach for Modeling and Inference -- 3.1 Preview -- 3.2 Mixed-Effects Models -- 3.2.1 The Model -- 3.2.2 Prediction -- 3.2.3 Model Fitting -- 3.2.4 Model Diagnostics -- 3.3 A Large-Sample Approach to Inference -- 3.3.1 Approximate Distributions -- 3.3.2 Confidence Intervals -- 3.3.3 Parameter Transformation -- 3.3.4 Bootstrap Confidence Intervals -- 3.3.5 Confidence Bands -- 3.3.6 Test of Homogeneity -- 3.3.7 Model Comparison -- 3.4 Modeling and Analysis of Method Comparison Data -- 3.5 Chapter Summary -- 3.6 Bibliographic Note -- Exercises -- 4 Paired Measurements Data -- 4.1 Preview -- 4.2 Modeling of Data -- 4.2.1 Mixed-Effects Model -- 4.2.2 Bivariate Normal Model -- 4.3 Evaluation of Similarity and Agreement -- 4.4 Case Studies -- 4.4.1 Oxygen Saturation Data -- 4.4.2 Plasma Volume Data -- 4.4.3 Vitamin D Data -- 4.5 Chapter Summary -- 4.6 Technical Details -- 4.6.1 Mixed-Effects Model -- 4.6.2 Bivariate Normal Model -- 4.7 Bibliographic Note -- Exercises -- 5 Repeated Measurements Data -- 5.1 Preview -- 5.2 Introduction -- 5.2.1 Types of Data -- 5.2.2 Individual versus Average Measurement -- 5.2.3 Example Datasets -- 5.3 Displaying Data -- 5.3.1 Basic Plots.
5.3.2 Interaction Plots -- 5.4 Modeling of Data -- 5.4.1 Unlinked Data -- 5.4.2 Linked Data -- 5.4.3 Model Fitting and Evaluation -- 5.5 Evaluation of Similarity and Agreement -- 5.6 Evaluation of Repeatability -- 5.6.1 Unlinked Data -- 5.6.2 Linked Data -- 5.7 Case Studies -- 5.7.1 Kiwi Data -- 5.7.2 Oximetry Data -- 5.8 Chapter Summary -- 5.9 Technical Details -- 5.9.1 Unlinked Data -- 5.9.2 Linked Data -- 5.10 Bibliographic Note -- Exercises -- 6 Heteroscedastic Data -- 6.1 Preview -- 6.2 Introduction -- 6.2.1 Diagnosing Heteroscedasticity -- 6.2.2 Example Datasets -- 6.3 Variance Function Models -- 6.4 Repeated Measurements Data -- 6.4.1 A Heteroscedastic Mixed-Effects Model -- 6.4.2 Specifying the Variance Function -- 6.4.3 Model Fitting and Evaluation -- 6.4.4 Testing for Homoscedasticity -- 6.4.5 Evaluation of Similarity, Agreement, and Repeatability -- 6.4.6 Case Study: Cholesterol Data -- 6.5 Paired Measurements Data -- 6.5.1 A Heteroscedastic Bivariate Normal Model -- 6.5.2 Specifying the Variance Function -- 6.5.3 Model Fitting and Evaluation -- 6.5.4 Testing for Homoscedasticity -- 6.5.5 Evaluation of Similarity and Agreement -- 6.5.6 Case Study: Cyclosporin Data -- 6.6 Chapter Summary -- 6.7 Technical Details -- 6.7.1 Repeated Measurements Data -- 6.7.2 Paired Measurements Data -- 6.8 Bibliographic Note -- Exercises -- 7 Data from Multiple Methods -- 7.1 Preview -- 7.2 Introduction -- 7.3 Displaying Data -- 7.4 Example Datasets -- 7.4.1 Systolic Blood Pressure Data -- 7.4.2 Tumor Size Data -- 7.5 Modeling Unreplicated Data -- 7.6 Modeling Repeated Measurements Data -- 7.6.1 Unlinked Data -- 7.6.2 Linked Data -- 7.7 Model Fitting and Evaluation -- 7.8 Evaluation of Similarity and Agreement -- 7.9 Evaluation of Repeatability -- 7.10 Case Studies -- 7.10.1 Systolic Blood Pressure Data -- 7.10.2 Tumor Size Data -- 7.11 Chapter Summary.
7.12 Technical Details -- 7.13 Bibliographic Note -- Exercises -- 8 Data with Covariates -- 8.1 Preview -- 8.2 Introduction -- 8.3 Modeling of Data -- 8.3.1 Modeling Means of Methods -- 8.3.2 Modeling Variances of Methods -- 8.3.3 Data Models -- 8.3.4 Model Fitting and Evaluation -- 8.4 Evaluation of Similarity, Agreement, and Repeatability -- 8.4.1 Measures of Agreement for Two methods -- 8.4.2 Measures of Agreement for More Than Two Methods -- 8.4.3 Measures of Repeatability -- 8.4.4 Inference on Measures -- 8.5 Case Study -- 8.6 Chapter Summary -- 8.7 Technical Details -- 8.8 Bibliographic Note -- Exercises -- 9 Longitudinal Data -- 9.1 Preview -- 9.2 Introduction -- 9.2.1 Displaying Data -- 9.2.2 Percentage Body Fat Data -- 9.3 Modeling of Data -- 9.3.1 The Longitudinal Data Model -- 9.3.2 Specifying the Mean Functions -- 9.3.3 Specifying the Correlation Function -- 9.3.4 Model Fitting and Evaluation -- 9.4 Evaluation of Similarity and Agreement -- 9.5 Case Study -- 9.6 Chapter Summary -- 9.7 Technical Details -- 9.8 Bibliographic Note -- Exercises -- 10 A Nonparametric Approach -- 10.1 Preview -- 10.2 Introduction -- 10.3 The Statistical Functional Approach -- 10.3.1 A Weighted Empirical CDF -- 10.3.2 Distributions Induced by Empirical CDF -- 10.4 Evaluation of Similarity and Agreement -- 10.5 Case Studies -- 10.5.1 Unreplicated Blood Pressure Data -- 10.5.2 Replicated Blood Pressure Data -- 10.6 Chapter Summary -- 10.7 Technical Details -- 10.7.1 The Matrix -- 10.7.2 Estimation of Ω -- 10.7.3 Influence Functions for the Measures -- 10.7.4 TDI Confidence Bounds -- 10.7.5 Summary of Steps -- 10.8 Bibliographic Note -- Exercises -- 11 Sample Size Determination -- 11.1 Preview -- 11.2 Introduction -- 11.3 The Sample Size Methodology -- 11.3.1 Paired Measurements Design -- 11.3.2 Repeated Measurements Design -- 11.4 Case Study.
11.5 Chapter Summary -- 11.6 Bibliographic Note -- Exercises -- 12 Categorical Data -- 12.1 Preview -- 12.2 Introduction -- 12.3 Experimental Setups and Examples -- 12.3.1 Types of Data -- 12.3.2 Illustrative Examples -- 12.3.3 A Graphical Approach -- 12.4 Cohen's Kappa Coefficient for Dichotomous Data -- 12.4.1 Definition and Basic Properties: Two Raters -- 12.4.2 Sample Kappa Coefficient -- 12.4.3 Agreement with a Gold Standard -- 12.4.4 Unbiased Raters: Intraclass Kappa -- 12.4.5 Multiple Raters -- 12.4.6 Combining and Comparing Kappa Coefficients -- 12.4.7 Sample Size Calculations -- 12.5 Kappa Type Measures for More Than Two Categories -- 12.5.1 Two Fixed Raters with Nominal Categories -- 12.5.2 Two Raters with Ordinal Categories: Weighted Kappa -- 12.5.3 Multiple Raters -- 12.6 Case Studies -- 12.6.1 Two Raters with Two Categories -- 12.6.2 Weighted Kappa: Multiple Categories -- 12.7 Models for Exploring Agreement -- 12.7.1 Conditional Logistic Regression Models -- 12.7.2 Log-Linear Models -- 12.7.3 A Generalized Linear Mixed-Effects Model -- 12.8 Discussion -- 12.9 Chapter Summary -- 12.10 Bibliographic Note -- Exercises -- References -- Dataset List -- Index -- EULA.
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Intro -- MEASURING AGREEMENT -- Contents -- Preface -- 1 Introduction -- 1.1 Preview -- 1.2 Notational Conventions -- 1.3 Basic Characteristics of a Measurement Method -- 1.3.1 A Statistical Model for Measurements -- 1.3.2 Quality Characteristics -- 1.4 Method Comparison Studies -- 1.5 Meaning of Agreement -- 1.6 A Measurement Error Model -- 1.6.1 Identifiability Issues -- 1.6.2 Model-Based Moments -- 1.6.3 Conditions for Perfect Agreement -- 1.6.4 Link to Test Theory -- 1.7 Similarity versus Agreement -- 1.7.1 Evaluation of Similarity -- 1.7.2 Evaluation of Agreement -- 1.8 A Toy Example -- 1.9 Controversies and Our View -- 1.10 Concepts Related to Agreement -- 1.11 Role of Confidence Intervals and Hypotheses Testing -- 1.11.1 Formulating the Agreement Hypotheses -- 1.11.2 Testing Hypotheses Using Confidence Bounds -- 1.11.3 Evaluation of Agreement Using Confidence Bounds -- 1.11.4 Evaluation of Similarity Using Confidence Intervals -- 1.12 Common Models for Paired Measurements Data -- 1.12.1 A Measurement Error Model -- 1.12.2 A MixedEffects Model -- 1.12.3 A Bivariate Normal Model -- 1.12.4 Limitations of the Paired Measurements Design -- 1.13 The Bland-Altman Plot -- 1.13.1 The Ideal Plot -- 1.13.2 A Linear Trend in the Bland-Altman Plot -- 1.13.3 Heteroscedasticity in the Bland-Altman Plot -- 1.13.4 Variations of the Bland-Altman Plot -- 1.14 Common Regression Approaches -- 1.14.1 Ordinary Linear Regression -- 1.14.2 Deming Regression -- 1.15 Inappropriate Use of Common Tests in Method Comparison Studies -- 1.15.1 Test of Zero Correlation -- 1.15.2 Paired t-test -- 1.15.3 Piviitman-Morgan and Bradley-Blackwood Tests -- 1.15.4 Test of Zero Intercept and Unit Slope -- 1.16 Key Steps in the Analysis of Method Comparison Data -- 1.17 Chapter Summary -- 1.18 Bibliographic Note -- Exercises -- 2 Common Approaches for Measuring Agreement.

2.1 Preview -- 2.2 Introduction -- 2.3 Mean Squared Deviation -- 2.4 Concordance Correlation Coefficient -- 2.5 A Digression: Tolerance and Prediction intervals -- 2.5.1 Definitions -- 2.5.2 Normally Distributed Data -- 2.6 Lin's Probability Criterion and Bland-Altman Criterion -- 2.7 Limits of Agreement -- 2.7.1 The Approach -- 2.7.2 Why Ignore the Variability? -- 2.7.3 Limits of Agreement versus Prediction and Tolerance Intervals -- 2.8 Total Deviation Index and Coverage Probability -- 2.8.1 The Approaches -- 2.8.2 Normally Distributed Differences -- 2.9 Inference on Agreement Measures -- 2.10 Chapter Summary -- 2.11 Bibliographic Note -- Exercises -- 3 A General Approach for Modeling and Inference -- 3.1 Preview -- 3.2 Mixed-Effects Models -- 3.2.1 The Model -- 3.2.2 Prediction -- 3.2.3 Model Fitting -- 3.2.4 Model Diagnostics -- 3.3 A Large-Sample Approach to Inference -- 3.3.1 Approximate Distributions -- 3.3.2 Confidence Intervals -- 3.3.3 Parameter Transformation -- 3.3.4 Bootstrap Confidence Intervals -- 3.3.5 Confidence Bands -- 3.3.6 Test of Homogeneity -- 3.3.7 Model Comparison -- 3.4 Modeling and Analysis of Method Comparison Data -- 3.5 Chapter Summary -- 3.6 Bibliographic Note -- Exercises -- 4 Paired Measurements Data -- 4.1 Preview -- 4.2 Modeling of Data -- 4.2.1 Mixed-Effects Model -- 4.2.2 Bivariate Normal Model -- 4.3 Evaluation of Similarity and Agreement -- 4.4 Case Studies -- 4.4.1 Oxygen Saturation Data -- 4.4.2 Plasma Volume Data -- 4.4.3 Vitamin D Data -- 4.5 Chapter Summary -- 4.6 Technical Details -- 4.6.1 Mixed-Effects Model -- 4.6.2 Bivariate Normal Model -- 4.7 Bibliographic Note -- Exercises -- 5 Repeated Measurements Data -- 5.1 Preview -- 5.2 Introduction -- 5.2.1 Types of Data -- 5.2.2 Individual versus Average Measurement -- 5.2.3 Example Datasets -- 5.3 Displaying Data -- 5.3.1 Basic Plots.

5.3.2 Interaction Plots -- 5.4 Modeling of Data -- 5.4.1 Unlinked Data -- 5.4.2 Linked Data -- 5.4.3 Model Fitting and Evaluation -- 5.5 Evaluation of Similarity and Agreement -- 5.6 Evaluation of Repeatability -- 5.6.1 Unlinked Data -- 5.6.2 Linked Data -- 5.7 Case Studies -- 5.7.1 Kiwi Data -- 5.7.2 Oximetry Data -- 5.8 Chapter Summary -- 5.9 Technical Details -- 5.9.1 Unlinked Data -- 5.9.2 Linked Data -- 5.10 Bibliographic Note -- Exercises -- 6 Heteroscedastic Data -- 6.1 Preview -- 6.2 Introduction -- 6.2.1 Diagnosing Heteroscedasticity -- 6.2.2 Example Datasets -- 6.3 Variance Function Models -- 6.4 Repeated Measurements Data -- 6.4.1 A Heteroscedastic Mixed-Effects Model -- 6.4.2 Specifying the Variance Function -- 6.4.3 Model Fitting and Evaluation -- 6.4.4 Testing for Homoscedasticity -- 6.4.5 Evaluation of Similarity, Agreement, and Repeatability -- 6.4.6 Case Study: Cholesterol Data -- 6.5 Paired Measurements Data -- 6.5.1 A Heteroscedastic Bivariate Normal Model -- 6.5.2 Specifying the Variance Function -- 6.5.3 Model Fitting and Evaluation -- 6.5.4 Testing for Homoscedasticity -- 6.5.5 Evaluation of Similarity and Agreement -- 6.5.6 Case Study: Cyclosporin Data -- 6.6 Chapter Summary -- 6.7 Technical Details -- 6.7.1 Repeated Measurements Data -- 6.7.2 Paired Measurements Data -- 6.8 Bibliographic Note -- Exercises -- 7 Data from Multiple Methods -- 7.1 Preview -- 7.2 Introduction -- 7.3 Displaying Data -- 7.4 Example Datasets -- 7.4.1 Systolic Blood Pressure Data -- 7.4.2 Tumor Size Data -- 7.5 Modeling Unreplicated Data -- 7.6 Modeling Repeated Measurements Data -- 7.6.1 Unlinked Data -- 7.6.2 Linked Data -- 7.7 Model Fitting and Evaluation -- 7.8 Evaluation of Similarity and Agreement -- 7.9 Evaluation of Repeatability -- 7.10 Case Studies -- 7.10.1 Systolic Blood Pressure Data -- 7.10.2 Tumor Size Data -- 7.11 Chapter Summary.

7.12 Technical Details -- 7.13 Bibliographic Note -- Exercises -- 8 Data with Covariates -- 8.1 Preview -- 8.2 Introduction -- 8.3 Modeling of Data -- 8.3.1 Modeling Means of Methods -- 8.3.2 Modeling Variances of Methods -- 8.3.3 Data Models -- 8.3.4 Model Fitting and Evaluation -- 8.4 Evaluation of Similarity, Agreement, and Repeatability -- 8.4.1 Measures of Agreement for Two methods -- 8.4.2 Measures of Agreement for More Than Two Methods -- 8.4.3 Measures of Repeatability -- 8.4.4 Inference on Measures -- 8.5 Case Study -- 8.6 Chapter Summary -- 8.7 Technical Details -- 8.8 Bibliographic Note -- Exercises -- 9 Longitudinal Data -- 9.1 Preview -- 9.2 Introduction -- 9.2.1 Displaying Data -- 9.2.2 Percentage Body Fat Data -- 9.3 Modeling of Data -- 9.3.1 The Longitudinal Data Model -- 9.3.2 Specifying the Mean Functions -- 9.3.3 Specifying the Correlation Function -- 9.3.4 Model Fitting and Evaluation -- 9.4 Evaluation of Similarity and Agreement -- 9.5 Case Study -- 9.6 Chapter Summary -- 9.7 Technical Details -- 9.8 Bibliographic Note -- Exercises -- 10 A Nonparametric Approach -- 10.1 Preview -- 10.2 Introduction -- 10.3 The Statistical Functional Approach -- 10.3.1 A Weighted Empirical CDF -- 10.3.2 Distributions Induced by Empirical CDF -- 10.4 Evaluation of Similarity and Agreement -- 10.5 Case Studies -- 10.5.1 Unreplicated Blood Pressure Data -- 10.5.2 Replicated Blood Pressure Data -- 10.6 Chapter Summary -- 10.7 Technical Details -- 10.7.1 The Matrix -- 10.7.2 Estimation of Ω -- 10.7.3 Influence Functions for the Measures -- 10.7.4 TDI Confidence Bounds -- 10.7.5 Summary of Steps -- 10.8 Bibliographic Note -- Exercises -- 11 Sample Size Determination -- 11.1 Preview -- 11.2 Introduction -- 11.3 The Sample Size Methodology -- 11.3.1 Paired Measurements Design -- 11.3.2 Repeated Measurements Design -- 11.4 Case Study.

11.5 Chapter Summary -- 11.6 Bibliographic Note -- Exercises -- 12 Categorical Data -- 12.1 Preview -- 12.2 Introduction -- 12.3 Experimental Setups and Examples -- 12.3.1 Types of Data -- 12.3.2 Illustrative Examples -- 12.3.3 A Graphical Approach -- 12.4 Cohen's Kappa Coefficient for Dichotomous Data -- 12.4.1 Definition and Basic Properties: Two Raters -- 12.4.2 Sample Kappa Coefficient -- 12.4.3 Agreement with a Gold Standard -- 12.4.4 Unbiased Raters: Intraclass Kappa -- 12.4.5 Multiple Raters -- 12.4.6 Combining and Comparing Kappa Coefficients -- 12.4.7 Sample Size Calculations -- 12.5 Kappa Type Measures for More Than Two Categories -- 12.5.1 Two Fixed Raters with Nominal Categories -- 12.5.2 Two Raters with Ordinal Categories: Weighted Kappa -- 12.5.3 Multiple Raters -- 12.6 Case Studies -- 12.6.1 Two Raters with Two Categories -- 12.6.2 Weighted Kappa: Multiple Categories -- 12.7 Models for Exploring Agreement -- 12.7.1 Conditional Logistic Regression Models -- 12.7.2 Log-Linear Models -- 12.7.3 A Generalized Linear Mixed-Effects Model -- 12.8 Discussion -- 12.9 Chapter Summary -- 12.10 Bibliographic Note -- Exercises -- References -- Dataset List -- Index -- EULA.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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