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Second‐order properties of intraclass correlation estimators for a symmetric normal distribution
Author(s) -
Pal Nabendu,
Lim Wooi K.
Publication year - 1999
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3315498
Subject(s) - intraclass correlation , estimator , mathematics , statistics , mean squared error , distribution (mathematics) , efficient estimator , trimmed estimator , minimum variance unbiased estimator , mathematical analysis , psychometrics
Consider the problem of estimating the intraclass correlation coefficient of a symmetric normal distribution under the squared error loss function. The general admissibility of the standard estimators of the intraclass correlation coefficient is hard to check due to their complicated sampling distributions. We follow the asymptotic decision‐theoretic approach of Ghosh and Sinha (1981) and prove that the three standard intraclass correlation estimators (the maximum‐likelihood estimator, the method‐of‐moments estimator and the first‐order unbiased estimator) are second‐order admissible for all p ≥ 2, p being the dimension of the distribution.