使用修正的肯德尔tau统计量检验双变量区间删失数据的独立性。

Testing independence of bivariate interval-censored data using modified Kendall's tau statistic.

作者信息

Kim Yuneung, Lim Johan, Park DoHwan

机构信息

Department of Statistics, Seoul National University, Seoul, Korea.

Department of Mathematics and Statistics, University of Maryland, Baltimore County, MD 21250, USA.

出版信息

Biom J. 2015 Nov;57(6):1131-45. doi: 10.1002/bimj.201300162. Epub 2015 Sep 15.

DOI:10.1002/bimj.201300162

PMID:26372502

Abstract

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).

摘要

在本文中，我们研究一种用于检验双变量区间删失数据独立性的非参数方法，适用于当前状态数据（情形1区间删失数据）和情形2区间删失数据。为此，我们针对双变量区间删失数据提出了基于得分的肯德尔tau统计量修正方法。我们的修正方法通过数据的一致对和不一致对的期望数量来定义肯德尔tau统计量。通过模拟研究以及在艾滋病研究中的应用，展示了修正方法的性能。我们将我们的方法与其他替代方法进行比较，比如Sun等人（《斯堪的纳维亚统计杂志》，2006年）提出的两阶段估计方法以及Betensky和Finkelstein（《医学统计学》，1999b）提出的多重填补方法。