Measuring Agreement: Models, Methods, and Applications


thumbnail image: Measuring Agreement: Models, Methods, and Applications
Measuring Agreement Methodology and Applications successfully blends the currently available statistical methodologies for agreement evaluation in a unified, coherent, and lucid manner.
This up-to-date and comprehensive book describes the theoretical underpinnings of the methodologies and presents case studies using several real data sets to illustrate the application of the methodologies. A perfect reference for statisticians, biostatisticians, clinical chemists, and biomedical scientists


Chapter 1: Introduction

1.1 Preview

1.2 Notational conventions

1.3 Basic characteristics of a measurement method

1.4 Method comparison studies

1.5 Meaning of agreement

1.6 A measurement error model

1.7 Similarity versus 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

1.12 Common models for paired measurements data

1.13 The Bland Altman plot

1.14 Common regression approaches

1.15 Inappropriate use of common tests in method comparison studies

1.16 Key steps in the analysis of method comparison data

1.17 Chapter summary

1.18 Bibliographic note


Chapter 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

2.6 Lin’s probability criterion and Bland Altman criterion

2.7 Limits of agreement

2.8 Total deviation index and coverage probability

2.9 Inference on agreement measures

2.10 Chapter summary

2.11 Bibliographic note


Chapter 3: A General Approach for Modeling and Inference

3.1 Preview

3.2 Mixed effects models

3.3 A large-sample approach for inference

3.4 Modeling and analysis of method comparison data

3.5 Chapter summary

3.6 Bibliographic note


Chapter 4: Paired Measurements Data

4.1 Preview

4.2 Modeling of data

4.3 Evaluation of similarity and agreement

4.4 Case studies

4.5 Chapter summary

4.6 Technical details

4.7 Bibliographic note


Chapter 5: Repeated Measurements Data

5.1 Preview

5.2 Introduction

5.3 Displaying data

5.4 Modeling of data

5.5 Evaluation of similarity and agreement

5.6 Evaluation of repeatability

5.7 Case studies

5.8 Chapter summary

5.9 Technical details

5.10 Bibliographic note


Chapter 6: Heteroscedastic Data

6.1 Preview

6.2 Introduction

6.3 Variance function models

6.4 Repeated measurements data

6.5 Paired measurements data

6.6 Chapter summary

6.7 Technical details

6.8 Bibliographic note


Chapter 7: Data from Multiple Methods

7.1 Preview

7.2 Introduction

7.3 Displaying data

7.4 Example datasets

7.5 Modeling unreplicated data

7.6 Modeling repeated measurements data

7.7 Model fitting and evaluation

7.8 Evaluation of similarity and agreement

7.9 Evaluation of repeatability

7.10 Case studies

7.11 Chapter summary

7.12 Technical details

7.13 Bibliographic note


Chapter 8: Data with Covariates

8.1 Preview

8.2 Introduction

8.3 Modeling of data

8.4 Evaluation of similarity, agreement and repeatability

8.5 Case study

8.6 Chapter summary

8.7 Technical details

8.8 Bibliographic note


Chapter 9: Longitudinal Data

9.1 Preview

9.2 Introduction

9.3 Modeling of data

9.4 Evaluation of similarity and agreement

9.5 Case study

9.6 Chapter summary

9.7 Technical details

9.8 Bibliographic note


Chapter 10: A Nonparametric Approach

10.1 Preview

10.2 Introduction

10.3 The statistical functional approach

10.4 Evaluation of similarity and agreement

10.5 Case studies

10.6 Chapter summary

10.7 Technical details

10.8 Bibliographic note


Chapter 11: Sample Size Determination

11.1 Preview

11.2 Introduction

11.3 The sample size methodology

11.4 Case study

11.5 Chapter summary

11.6 Bibliographic note


Chapter 12: Categorical Data

12.1 Preview

12.2 Introduction

12.3 Experimental setups and examples

12.4 Cohen’s kappa coefficient for dichotomous data

12.5 Kappa type measures for more than two categories

12.6 Case studies

12.7 Models for exploring agreement

12.8 Discussion

12.9 Chapter summary

12.10 Bibliographic note



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Published features on are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.