Testing independence for bivariate current status data

A. Adam Ding*, Weijing Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

This article develops a nonparametric procedure for testing marginal independence based on bivariate current status data. Asymptotic properties of the proposed tests are derived, and their finite-sample performance is studied via simulations. The method is applied to analyze data from a community-based study of cardiovascular epidemiology in Taiwan.

Original languageEnglish
Pages (from-to)145-155
Number of pages11
JournalJournal of the American Statistical Association
Volume99
Issue number465
DOIs
StatePublished - 1 Mar 2004

Keywords

  • Cochran–Mantel–Haenszel test
  • Epidemiology
  • Interval censoring
  • Lifetime data
  • Nonparametric analysis
  • Two-by-two table

Fingerprint Dive into the research topics of 'Testing independence for bivariate current status data'. Together they form a unique fingerprint.

Cite this