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A class of weighted dependence measures for bivariate failure time data
Author(s) -
Fan J.,
Prentice R. L.,
Hsu L.
Publication year - 2000
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/1467-9868.00227
Subject(s) - bivariate analysis , estimator , mathematics , nonparametric statistics , statistics , variance (accounting) , class (philosophy) , measure (data warehouse) , function (biology) , econometrics , computer science , accounting , database , artificial intelligence , evolutionary biology , business , biology
This paper considers a class of summary measures of the dependence between a pair of failure time variables over a finite follow‐up region. The class consists of measures that are weighted averages of local dependence measures, and includes the cross‐ratio‐measure and finite region version of Kendall's τ; recently proposed by the authors. Two new special cases are identified that can avoid the need to estimate the bivariate survivor function and that admit explicit variance estimators. Nonparametric estimators of such dependence measures are proposed and are shown to be consistent and asymptotically normal with variances that can be consistently estimated. Properties of selected estimators are evaluated in a simulation study, and the method is illustrated through an analysis of Australian Twin Study data.