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Measures of agreement for vectorcardiography data
Author(s) -
Wang Haonan
Publication year - 2009
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3519
Subject(s) - measure (data warehouse) , mathematics , nonparametric statistics , vectorcardiography , rotation (mathematics) , statistics , data set , concordance correlation coefficient , percentile , interval (graph theory) , computer science , data mining , combinatorics , geometry , medicine , cardiology , electrocardiography
In this paper, nonparametric methods are proposed for quantifying agreement and disagreement between different measurement methods when the results of the measurements are rotation matrices. First, the expected squared distance between two matrices is used to quantify the measurement agreement. Two choices of such distance are considered—the Frobenius distance and geodesic distance. Second, the notion of ‘concordance correlation coefficient’, a commonly used measure of agreement, is extended to the space of rotation matrices. Such generalized concordance coefficient can be treated as a normalized expected squared distance. Since no two measurement systems can be expected to be in perfect agreement, it becomes necessary to define a notion of practical agreement. We define such a notion. Moreover, for both proposed methods, the percentile bootstrap procedure is implemented to provide a confidence interval to help make a decision concerning practical agreement/disagreement in real‐life applications. The methodology is illustrated using two data sets, one based on an application involving vectorcardiography data ( Biometrika 1972; 59 :665–676) and the other based on a synthetic data set. Copyright © 2009 John Wiley & Sons, Ltd.