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Activity Number: 386 - Nonparametric Modeling II
Type: Contributed
Date/Time: Thursday, August 12, 2021 : 12:00 PM to 1:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #317709
Title: Effect of Trimming on Robust Measures of Agreement
Author(s): Elahe Tashakor*
Companies: Ipsos Public Affairs
Keywords: L-statistics; Non parametrics; agreement coefficient
Abstract:

In many social and clinical studies, Lin’s (1989) concordance correlation coefficient (CCC) is a popular measure of agreement for continuous outcomes. Most commonly, it is used under the assumption that data are normally distributed. However, in many practical applications, data are often skewed and/or thick-tailed. Tashakor and Chinchilli(2018) proposed robust estimation methods of alternative CCC indices by focusing on functionals that yield robust L-statistics. They used Trimmed mean and Winsorized mean as fuctionals of L-statistics. In this work, we investigate the effect of different degrees of trimming on the bias and coverage probability of the proposed robust coefficient. We provide two data examples to illustrate the methodology, and we discuss the results of computer simulation studies that evaluate statistical performance.


Authors who are presenting talks have a * after their name.

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