Exact tests for exponential regression

Ori Davidov, Marvin Zelen

Research output: Contribution to journalArticlepeer-review


The exponential distribution is a fundamental model in parametric survival analysis. In this paper the exponential regression model with a canonical parameterization, λ=βtx, is explored. Large sample and exact significance tests are developed to test the relationship between survival and one covariate. The standard unconditional likelihood approach is compared with two new tests, which are based on the conditional distribution of the sufficient statistics. The various testing procedures are compared numerically. Finally, the relationship with the semiparametric proportional hazard model is investigated.

Original languageEnglish
Pages (from-to)87-97
Number of pages11
JournalJournal of Statistical Planning and Inference
Issue number1
StatePublished - 1 Jul 2000

Bibliographical note

Funding Information:
This work was partially supported by grants from the National Cancer Institute and National Institutes of Health.


  • 62J05
  • 62J12
  • Conditional inference
  • Exact tests
  • Exponential regression

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics


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