Emura, Takeshi and Wang, Weijing (2009): Testing Quasiindependence for Truncation Data. Published in: Journal of Multivariate Analysis , Vol. 101, (January 2010): pp. 223239.

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Abstract
Quasiindependence is a common assumption for analyzing truncated data. To verify this condition, we propose a class of weighted logrank type statistics that includes existing tests proposed by Tsai (1990) and Martin and Betensky (2005) as special cases. To choose an appropriate weight function that may lead to a more power test, we derive a score test when the dependence structure under the alternative hypothesis is modeled via the odds ratio function proposed by Chaieb, Rivest and Abdous (2006). Asymptotic properties of the proposed tests are established based on the functional delta method which can handle more general situations than results based on rankstatistics or Ustatistics. Extension of the proposed methodology under two different censoring settings is also discussed. Simulations are performed to examine finitesample performances of the proposed method and its competitors. Two datasets are analyzed for illustrative purposes.
Item Type:  MPRA Paper 

Original Title:  Testing Quasiindependence for Truncation Data 
Language:  English 
Keywords:  Conditional likelihood; Kendall’s tau; MantelHeanszel test; Power; Rightcensoring; Survival data; Twobytwo table 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C12  Hypothesis Testing: General 
Item ID:  58582 
Depositing User:  takeshi emura 
Date Deposited:  17 Sep 2014 04:32 
Last Modified:  28 Sep 2019 17:08 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/58582 