کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
415518 681214 2007 22 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Improving the estimation of Kendall's tau when censoring affects only one of the variables
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Improving the estimation of Kendall's tau when censoring affects only one of the variables
چکیده انگلیسی

This paper considers the estimation of Kendall's tau for bivariate data (X,Y)(X,Y) when only Y   is subject to right-censoring. Although ττ is estimable under weak regularity conditions, the estimators proposed by Brown et al. [1974. Nonparametric tests of independence for censored data, with applications to heart transplant studies. Reliability and Biometry, 327–354], Weier and Basu [1980. An investigation of Kendall's ττ modified for censored data with applications. J. Statist. Plann. Inference 4, 381–390] and Oakes [1982. A concordance test for independence in the presence of censoring. Biometrics 38, 451–455], which are standard in this context, fail to be consistent when τ≠0τ≠0 because they only use information from the marginal distributions. An exception is the renormalized estimator of Oakes [2006. On consistency of Kendall's tau under censoring. Technical Report, Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY], whose consistency has been established for all possible values of ττ, but only in the context of the gamma frailty model. Wang and Wells [2000. Estimation of Kendall's tau under censoring. Statist. Sinica 10, 1199–1215] were the first to propose an estimator which accounts for joint information. Four more are developed here: the first three extend the methods of Brown et al. [1974. Nonparametric tests of independence for censored data, with applications to heart transplant studies. Reliability and Biometry, 327–354], Weier and Basu [1980, An investigation of Kendall's ττ modified for censored data with applications. J. Statist. Plann. Inference 4, 381–390] and Oakes [1982, A concordance test for independence in the presence of censoring. Biometrics 38, 451–455] to account for information provided by X  , while the fourth estimator inverts an estimation of Pr(Yi⩽y|Xi=xi,Yi>ci)Pr(Yi⩽y|Xi=xi,Yi>ci) to get an imputation of the value of YiYi censored at Ci=ciCi=ci. Following Lim [2006. Permutation procedures with censored data. Comput. Statist. Data Anal. 50, 332–345], a nonparametric estimator is also considered which averages the τ^i obtained from a large number of possible configurations of the observed data (X1,Z1),…,(Xn,Zn)(X1,Z1),…,(Xn,Zn), where Zi=min(Yi,Ci)Zi=min(Yi,Ci). Simulations are presented which compare these various estimators of Kendall's tau. An illustration involving the well-known Stanford heart transplant data is also presented.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 12, 15 August 2007, Pages 5743–5764
نویسندگان
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