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A generalized log‐rank test for interval‐censored failure time data via multiple imputation
Author(s) -
Huang Jinlong,
Lee Chinsan,
Yu Qiqing
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3211
Subject(s) - statistics , mathematics , covariance matrix , estimator , biometrics , test statistic , imputation (statistics) , covariance , confidence interval , statistical hypothesis testing , missing data , computer science , artificial intelligence
Interval‐censored (IC) failure time data often occur in follow‐up studies where subjects can only be followed periodically and the failure time can only be known to lie in an interval. In this paper we propose a modified log‐rank test for the problem of comparing two or more IC samples. Our log‐rank statistic and covariance matrix are calculated by a multiple imputation technique. Through simulation studies, we find that the performance of the proposed test is comparable to that of the test proposed by Finkelstein ( Biometrics 1986; 42 (4):845–854) and is better than that of the two existing log‐rank type tests proposed by Sun ( Lifetime Data Anal . 2001; 7 :363–375) and Zhao and Sun ( Stat. Med . 2004; 23 (10):1621–1629) due to the differences in the method of multiple imputation and the covariance matrix estimation. Our covariance matrix estimator is similar to the estimator used by Follmann et al . ( Biometrics 2003; 59 :420–429) for clustered data. The proposed method is illustrated by means of an example involving patients with breast cancer. Copyright © 2008 John Wiley & Sons, Ltd.