Measures of Interobserver Agreement and Reliability
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 over theory, Measure of Interobserver Agreement provides a comprehensive survey of this method and includes standards and directions on how to run sound reliability and agreement studies in clinical settings and other types of investigations.
The author clearly explains how to reduce measurement error, presents numerous practical examples of the interobserver agreement approach, and emphasizes measures of agreement among raters for categorical assessments. The models and methods are considered in two different but closely related contexts: 1) assessing agreement among several raters where the response variable is continuous and 2) where there is a prior decision by the investigators to use categorical scales to judge the subjects enrolled in the study. While the author thoroughly discusses the practical and theoretical issues of case 1, a major portion of this book is devoted to case 2. He explores issues such as two raters randomly judging a group of subjects, interrater bias and its connection to marginal homogeneity, and statistical issues in determining sample size.
Statistical analysis of real and hypothetical datasets are presented to demonstrate the various applications of the models in repeatability and validation studies. To help with problem solving, the monograph includes SAS code, both within the book and on the CRC Web site. The author presents information with the right amount mathematical details, making this a cohesive book that reflects new research and the latest developments in the field.
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chapter 1 Introduction
chapter 2 Reliability for continuous scale measurements
chapter 3 Measure of 2x2 association and agreement of crossclassified data
chapter 4 Coefficients of agreement for multiple raters and multiple categories
chapter 5 Assessing agreement from dependent data
chapter 6 Sample size requirements for the design of a reliability study
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ANOVA assessments assumed asymptotic variance binary Chapter chi-square chi-square distribution Class Level classification clinical Conf Limit confidence interval cost covariates Data Layout degrees of freedom denote depends dichotomous Equation error evaluation example F Value Pr ffff:ffff:ffff:ffff:ffff:ffff:fff Fleiss ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ Total G_55 primary given interrater agreement interrater bias intraclass correlation coefficient ith subject kappa statistic Linear Models Linear Models Procedure log-linear models marginal probability McNemar's Test measure of agreement methods multiple raters null hypothesis number of replicates number of subjects one-way random effects optimal p-value parameter patients Percent R R R R random effects model rater1 by rater2 raters ratings reliability study Row Pct sample score Shoukri Simple Kappa Coefficient Source DF Type Square F Value SS Mean Square STATISTICS FOR TABLE Table of rater1 TABLE OF ULTRA Total ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ type I error ULTRA BY MRI Var(Error Variable Workshop