Handbook Of Inter Rater Reliability The Definitive Guide To Measuring The Extent Of Agreement Among Raters

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.

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.

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.

This proceedings book highlights the latest research and developments in psychometrics and statistics. Featuring contributions presented at the 82nd Annual Meeting of the Psychometric Society (IMPS), organized by the University of Zurich and held in Zurich, Switzerland from July 17 to 21, 2017, its 34 chapters address a diverse range of psychometric topics including item response theory, factor analysis, causal inference, Bayesian statistics, test equating, cognitive diagnostic models and multistage adaptive testing. The IMPS is one of the largest international meetings on quantitative measurement in psychology, education and the social sciences, attracting over 500 participants and 250 paper presentations from around the world every year. This book gathers the contributions of selected presenters, which were subsequently expanded and peer-reviewed.

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.

This volume collects the extended versions of papers presented at the SIS Conference “Statistics and Data Science: new challenges, new generations”, held in Florence, Italy on June 28-30, 2017. Highlighting the central role of statistics and data analysis methods in the era of Data Science, the contributions offer an essential overview of the latest developments in various areas of statistics research. The 35 contributions have been divided into six parts, each of which focuses on a core area contributing to “Data Science”. The book covers topics including strong statistical methodologies, Bayesian approaches, applications in population and social studies, studies in economics and finance, techniques of sample design and mathematical statistics. Though the book is mainly intended for researchers interested in the latest frontiers of Statistics and Data Analysis, it also offers valuable supplementary material for students of the disciplines dealt with here. Lastly, it will help Statisticians and Data Scientists recognize their counterparts’ fundamental role.

This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at the 10th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2015), held in the beautiful and historic city of Burgos (Spain), in June 2015. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate and analyze very complex issues and phenomena. This Conference is mainly focused on its industrial and environmental applications. After a through peer-review process, the SOCO 2015 International Program Committee selected 41 papers, written by authors from 15 different countries. These papers are published in present conference proceedings, achieving an acceptance rate of 40%. The selection of papers was extremely rigorous in order to maintain the high quality of the conference and we would like to thank the members of the International Program Committees for their hard work during the review process. This is a crucial issue for creation of a high standard conference and the SOCO conference would not exist without their help.