Testing quasi-independence for doubly truncated data
Testing quasi-independence for doubly truncated data
复制标题
测试双截断数据的准独立性
DOI：
10.1080/10485252.2011.564280
复制
发表时间：
2011
影响因子：
1.2
通讯作者：
P. Shen
中科院分区：
文献类型：
--
作者：
P. Shen
双截断数据出现在许多应用中，包括天文学和生存分析。拟独立性是分析双截尾数据的常见假设。为了验证这个条件，使用Emura和Wang [（2010），'Testing Quasi-independence for Truncation Data'，Journal of Multivariate Analysis，101，223-293]的方法，我们提出了一类加权对数秩型统计量。给出了检验的渐近分布理论。通过Monte Carlo模拟，将所提出的检验的性能与Martin和Betensky [（2005），'Testing Quasi-independence of Failure and Truncation Via Conditional Kendall's Tau'，Journal of the American Statistical Association，100，484-492]提出的现有检验进行比较。
Doubly truncated data appear in a number of applications, including astronomy and survival analysis. Quasi-independence is a common assumption for analysing double-truncated data. To verify this condition, using the approach of Emura and Wang [(2010), ‘Testing Quasi-independence for Truncation Data’, Journal of Multivariate Analysis, 101, 223–293], we propose a class of weighted log-rank-type statistics. The asymptotic distribution theory of the test is presented. The performance of the proposed test is compared with the existing test proposed by Martin and Betensky [(2005), ‘Testing Quasi-independence of Failure and Truncation Via Conditional Kendall's Tau’, Journal of the American Statistical Association, 100, 484–492], by means of Monte Carlo simulations.