A Unified Model for Continuous and Categorical Data

Lawrence Lin (), A. S. Hedayat () and Wenting Wu ()
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Lawrence Lin: Baxter International Inc.
A. S. Hedayat: University of Illinois, Chicago, Department of Mathematics, Statistics and Computer Science
Wenting Wu: Mayo Clinic

Chapter Chapter 5 in Statistical Tools for Measuring Agreement, 2012, pp 75-110 from Springer

Abstract: Abstract In this chapter, we generalize agreement assessment for continuous and categorical data to cover multiple raters (k ≥ 2), and each with multiple readings (m ≥ 1) from each of the n subjects. In Chapters 2 and 3, we discussed agreement statistics for continuous and categorical data, respectively, based on the basic model of two raters with a single measure each per subject. In the terminology of this chapter, those earlier chapters discussed primarily the case k = 2 and m = 1. We utilize the results from Barnhart, Song, and Haber (2005), who first proposed the within-rater CCC, between-rater CCC based on the average of replicates, and between-rater CCC based on individual replicate, and used GEE methodology for estimation and statistical inference. We then combine the GEE methodology with the knowledge gained from Robieson (1999) and Carrasco and Jover (2003), and propose a unified approach that is applicable to continuous and categorical data.

Keywords: Variance Component; Weighted Kappa; Total Deviation; Interrater Agreement; Agreement Statistic (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-0562-7_5

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DOI: 10.1007/978-1-4614-0562-7_5

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