Handbook Of Inter Rater Reliability The Definitive Guide To Measuring The Extent Of Agreement Among Raters Vol 2 Analysis Of Quantitative Ratings

Low inter-rater reliability can jeopardize the integrity of scientific inquiries or have dramatic consequences in practice. In a clinical setting for example, a wrong drug or wrong dosage of the correct drug may be administered to patients at a hospital due to a poor diagnosis. Likewise, exam grades are considered reliable if they are determined only by the candidate's proficiency level in a particular skill, and not by the examiner's scoring method. The study of inter-rater reliability helps researchers address these issues using an approach that is methodologically sound. The 4th edition of this book covers Chance-corrected Agreement Coefficients (CAC) for the analysis of categorical ratings, as well as Intraclass Correlation Coefficients (ICC) for the analysis of quantitative ratings. The 5th edition however, is released in 2 volumes. The present volume 2, focuses on ICC methods whereas volume 1 is devoted to CAC methods. The decision to release 2 volumes was made at the request of numerous readers of the 4th edition who indicated that they are often interested in either CAC techniques or in ICC techniques, but rarely in both at a given point in time. Moreover, the large number of topics covered in this 5th edition could not be squeezed in a single book, without it becoming voluminous. Volume 2 of the Handbook of Inter-Rater Reliability 5th edition contains 2 new chapters not found in the previous editions, and updated versions of 7 chapters taken from the 4th edition. Here is a summary of the main changes from the 4th edition that you will find in this book: Chapter 2 is new to the 5th edition and covers various ways of setting up your rating dataset before analysis. Chapter 3 is introductory and an update of chapter 7 in the 4th edition. In addition to providing an overview of the book content similar to that of the 4th edition, this chapter introduces the new multivariate intraclass correlation not covered in previous editions. Chapter 4 covers intraclass correlation coefficients in one-factor models and has a separate section devoted to sample size calculations. Two approaches to sample size calculations are now offered: the statistical power approach and the confidence interval approach. Chapter 5 covers intraclass correlation coefficients under the random factorial design, which is based on a two-way Analysis of Variance model where the rater and subject factors are both random. Section 5.4 on sample size calculations has been expanded substantially. Researchers can now choose between the statistical power approach based on the Minimum Detectable Difference (MDD) and the confidence interval approach based on the target interval length. Chapter 6 covers intraclass correlation coefficients under the mixed factorial design, which is based on a two-way Analysis of Variance model where the rater factor is fixed and the subject factor random. The treatment of sample size calculations has been expanded substantially. Chapter 7 is new and covers Finn's coefficient of reliability as an alternative to the traditional intraclass correlations when they are not be applicable. Chapter 8 entitled "Measures of Association and Concordance" covers various association and concordance measures often used by researchers. It includes a discussion of Lin's concordance correlation coefficient and its statistical properties. Chapter 9 is new and covers 3 important topics: the benchmarking of ICC estimates, a graphical approach for exploring the influence of individual raters in low-agreement inter-rater reliability experiments, and the multivariate intraclass correlation. I wanted this book to be sufficiently detailed for practitioners to gain more insight into the topics, which would not be possible if the book was limited to a high-level coverage of technical concepts.

By writing the third edition of the Handbook of Inter-Rater Reliability, my primary goal was to allow researchers and students in all fields of research to be able to access in one place, detailed, well-organized, and readable materials on inter-rater reliability assessment. Chance-corrected agreement coefficients are covered in part I of the book, while part II is devoted to agreement coefficients in the family of intraclass correlations. Part III covers several rank-based measures of association, in addition to discussing agreement within the framework of item analysis. The methods and techniques developed in this edition of the handbook of inter-rater reliability can handle missing ratings, which are common in most experiments. This is an improvement over the second edition, which describes the methods for complete data sets only. Part II and Part III contain new chapters aimed at providing researchers with a broader coverage of inter-rater reliability techniques. Even chance-corrected agreement coefficients, already covered in the second edition, are presented in the current edition with more depth and more clarity. I wanted to ensure that the content of this book is accessible to readers with no background in statistics. Based on feedback I received about earlier editions of this book, this goal appears to have been achieved to a large extent. I expect the Handbook of Inter-Rater Reliability to be an essential reference on inter-rater reliability assessment to all researchers, students, and practitioners in all fields of research.

This book presents various methods for calculating the extent of agreement among raters for different types of ratings. Some of the methods initially developed for nominal-scale ratings only, are extended in this book to ordinal and interval scales as well. To ensure an adequate level of sophistication in the treatment of this topic, the precision aspects associated with the agreement coefficients are treated. New methods begin with the simple scenario of 2 raters and 2 response categories before being extended to the more complex situation of multiple raters, and multiple-level nominal, ordinal and interval scales. Cohen's Kappa coefficient is one of the most widely-used agreement coefficients among researchers, despite its tendency to yield controvertial results. Kappa and its various versions have raised concerns among practitioners and showed limitations, which are well-documented in the literature. This book discusses numerous alternatives, and proposes a new framework of analysis that allows researchers to gain further insight into the core issues related to the interpretation of the coefficients' magnitude, in addition to providing a common framework for evaluating the merit of different approaches. The author explains in a clear and intuitive fashion the motivations and assumptions underlying each technique discussed in the book. He demonstrates the benefits of using basic level statistical thinking in the design and analysis of inter-rater reliability experiments. The interpretation and limitations of various techniques are extensively discussed. From optimizing the design of the inter-rater reliability study to validating the computed agreement coefficients, the author's step-by-step approach is practical, easy to understand and will put all practitioners on the path to achieving their data quality objectives.

The third edition of this book was very well received by researchers working in many different fields of research. The use of that text also gave these researchers the opportunity to raise questions, and express additional needs for materials on techniques poorly covered in the literature. For example, when designing an inter-rater reliability study, many researchers wanted to know how to determine the optimal number of raters and the optimal number of subjects that should participate in the experiment. Also, very little space in the literature has been devoted to the notion of intra-rater reliability, particularly for quantitative measurements. The fourth edition of this text addresses those needs, in addition to further refining the presentation of the material already covered in the third edition. Features of the Fourth Edition include: New material on sample size calculations for chance-corrected agreement coefficients, as well as for intraclass correlation coefficients. The researcher will be able to determine the optimal number raters, subjects, and trials per subject.The chapter entitled “Benchmarking Inter-Rater Reliability Coefficients” has been entirely rewritten.The introductory chapter has been substantially expanded to explore possible definitions of the notion of inter-rater reliability.All chapters have been revised to a large extent to improve their readability.

Agreement among raters is of great importance in many domains. For example, in medicine, diagnoses are often provided by more than one doctor to make sure the proposed treatment is optimal. In criminal trials, sentencing depends, among other things, on the complete agreement among the jurors. In observational studies, researchers increase reliability by examining discrepant ratings. This book is intended to help researchers statistically examine rater agreement by reviewing four different approaches to the technique. The first approach introduces readers to calculating coefficients that allow one to summarize agreements in a single score. The second approach involves estimating log-linear models that allow one to test specific hypotheses about the structure of a cross-classification of two or more raters' judgments. The third approach explores cross-classifications or raters' agreement for indicators of agreement or disagreement, and for indicators of such characteristics as trends. The fourth approach compares the correlation or covariation structures of variables that raters use to describe objects, behaviors, or individuals. These structures can be compared for two or more raters. All of these methods operate at the level of observed variables. This book is intended as a reference for researchers and practitioners who describe and evaluate objects and behavior in a number of fields, including the social and behavioral sciences, statistics, medicine, business, and education. It also serves as a useful text for graduate-level methods or assessment classes found in departments of psychology, education, epidemiology, biostatistics, public health, communication, advertising and marketing, and sociology. Exposure to regression analysis and log-linear modeling is helpful.

Agreement among at least two evaluators is an issue of prime importance to statisticians, clinicians, epidemiologists, psychologists, and many other scientists. Measuring interobserver agreement is a method used to evaluate inconsistencies in findings from different evaluators who collect the same or similar information. Highlighting applications o

This introductory book enables researchers and students of all backgrounds to compute interrater agreements for nominal data. It presents an overview of available indices, requirements, and steps to be taken in a research project with regard to reliability, preceded by agreement. The book explains the importance of computing the interrater agreement and how to calculate the corresponding indices. Furthermore, it discusses current views on chance expected agreement and problems related to different research situations, so as to help the reader consider what must be taken into account in order to achieve a proper use of the indices. The book offers a practical guide for researchers, Ph.D. and master students, including those without any previous training in statistics (such as in sociology, psychology or medicine), as well as policymakers who have to make decisions based on research outcomes in which these types of indices are used.