A Monte Carlo Power Study of Logrank, Wilcoxon and Normal Scores Procedures on Matched and Censored Data

Joel E. Michalek, Daniel Mihalko, Thomas J. White

Research output: Contribution to journalArticle

Abstract

The powers of several nonparametric tests for determining a treatment effect using matched censored data are compared by simulation. The tests include adaptations of two sample Prentice efficient score extensions of the Exponential Scores, Wilcoxon and Normal Scores tests with three different variance estimators. The tests are compared on simulated exponential, loglogistic and lognormal matched censored data. No test performed uniformly better than the others. However the Exponential Scores, or Logrank, test using the permutation or hypergeometric variance seemed to be more powerful in quite a few situations as well as having other advantages.

Original languageEnglish (US)
Pages (from-to)449-465
Number of pages17
JournalCommunications in Statistics - Simulation and Computation
Volume14
Issue number2
DOIs
StatePublished - Jan 1 1985

Keywords

  • Wilcoxon test normal score. test Censored data matched data. Monte. Carlo Study logrank tests

ASJC Scopus subject areas

  • Modeling and Simulation
  • Statistics and Probability

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