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Bias reduction for nonparametric correlation coefficients under the bivariate normal copula assumption with known detection limits
Author(s) -
Nie Lei,
Chu Haitao,
Korostyshevskiy Valeriy R.
Publication year - 2008
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 - 10.1002/cjs.5550360307
Subject(s) - bivariate analysis , copula (linguistics) , mathematics , nonparametric statistics , censoring (clinical trials) , statistics , correlation , gaussian , econometrics , physics , geometry , quantum mechanics
The authors derive the asymptotic mean and bias of Kendall's tau and Spearman's rho in the presence of left censoring in the bivariate Gaussian copula model. They show that tie corrections for left‐censoring brings the value of these coefficients closer to zero. They also present a bias reduction method and illustrate it through two applications.