Testing quasi-independence for truncation data

Takeshi Emura, Wei-Jing Wang*

*Corresponding author for this work

Research output: Contribution to journalArticle

16 Scopus citations

Abstract

Quasi-independence is a common assumption for analyzing truncated data. To verify this condition, we propose a class of weighted log-rank type statistics that include 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 rank-statistics or U-statistics. Extension of the proposed methodology under two different censoring settings is also discussed. Simulations are performed to examine finite-sample performances of the proposed method and its competitors. Two datasets are analyzed for illustrative purposes.

Original languageEnglish
Pages (from-to)223-239
Number of pages17
JournalJournal of Multivariate Analysis
Volume101
Issue number1
DOIs
StatePublished - 1 Jan 2010

Keywords

  • Conditional likelihood
  • Kendall's tau
  • Mantel-Haenszel test
  • Power
  • Right-censoring
  • Survival data
  • Two-by-two table

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