Tests of independence for bivariate data with random censoring: A contingency-table approach

M. G. Akritas, C. C. Clogg

Research output: Contribution to journalReview article

1 Citation (Scopus)

Abstract

Procedures are proposed for testing the hypothesis of independence between two discrete or discretized random variables, one or both of which may be randomly censored. The censoring mechanisms can be either independent (bivariate censoring) or identical (univariate censoring). The proposed tests reduce to goodness-of-fit tests for log-linear models applied to either complete or incomplete contingency tables. Three examples are analyzed for illustrative purposes.

Original languageEnglish (US)
Pages (from-to)1339-1354
Number of pages16
JournalBiometrics
Volume47
Issue number4
DOIs
StatePublished - Jan 1 1991

Fingerprint

Random Censoring
Test of Independence
Contingency Table
Censoring
Random variables
Linear Models
Testing
Log-linear Models
testing
Goodness of Fit Test
Univariate
Random variable
linear models

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Cite this

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Tests of independence for bivariate data with random censoring : A contingency-table approach. / Akritas, M. G.; Clogg, C. C.

In: Biometrics, Vol. 47, No. 4, 01.01.1991, p. 1339-1354.

Research output: Contribution to journalReview article

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