Statistical methods in assessing agreement: Models, issues, and tools

• 成果类型: Article
• 署名作者: Lin, L; Hedayat, AS; Sinha, B; Yang, M
• 署名单位: University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Indian Statistical Institute; Indian Statistical Institute Kolkata
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/016214502753479392
• 发表日期: 2002
• 页码: 257-270
• 关键词: concordance correlation-coefficient; individual bioequivalence; evaluate reproducibility; population

摘要

Measurements of agreement are needed to assess the acceptability of a new or generic process, methodology, and formulation in areas of laboratory performance, instrument or assay validation, method comparisons, statistical process control, goodness of fit, and individual bioequivalence, In all of these areas, one needs measurements that capture a large proportion of data that are within a meaningful boundary from target values. Target values can be considered random (measured with error) or fixed (known), depending on the situation. Various meaningful measures to cope with such diverse and complex situations have become available only in the last decade. These measures often assume that the target values are random, This article reviews the literature and presents methodologies in terms of coverage probability. In addition, analytical expressions are introduced for all of the aforementioned measurements when the target values are fixed and when the error structure is homogenous or heterogeneous (proportional to target values). This article compares the asymptotic power of accepting the agreement across all competing methods and discusses the pros and cons of each. Data when the target values ire random or fixed are used for illustration. A SAS macro program to compute all of the proposed methods is available for download at http://www.uic.edu/similar tohedayat/.