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Testing independence of bivariate interval‐censored data using modified Kendall's tau statistic
Author(s) -
Kim Yuneung,
Lim Johan,
Park DoHwan
Publication year - 2015
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201300162
Subject(s) - statistics , bivariate analysis , nonparametric statistics , mathematics , statistic , test statistic , econometrics , imputation (statistics) , confidence interval , statistical hypothesis testing , missing data
In this paper, we study a nonparametric procedure to test independence of bivariate interval censored data; for both current status data (case 1 interval‐censored data) and case 2 interval‐censored data. To do it, we propose a score‐based modification of the Kendall's tau statistic for bivariate interval‐censored data. Our modification defines the Kendall's tau statistic with expected numbers of concordant and disconcordant pairs of data. The performance of the modified approach is illustrated by simulation studies and application to the AIDS study. We compare our method to alternative approaches such as the two‐stage estimation method by Sun et al. (Scandinavian Journal of Statistics, 2006) and the multiple imputation method by Betensky and Finkelstein (Statistics in Medicine, 1999b).