A new paradigm for hypothesis testing in medicine, with examination of the Neyman Pearson condition

G. William Moore, Grover M. Hutchins, Robert E. Miller

Research output: Contribution to journalArticle

Abstract

In the past, hypothesis testing in medicine has employed the paradigm of the repeatable experiment. In statistical hypothesis testing, an unbiased sample is drawn from a larger source population, and a calculated statistic is compared to a preassigned critical region, on the assumption that the comparison could be repeated an indefinite number of times. However, repeated experiments often cannot be performed on human beings, due to ethical or economic constraints. We describe a new paradigm for hypothesis testing which uses only rearrangements of data present within the observed data set. The token swap test, based on this new paradigm, is applied to three data sets from cardiovascular pathology, and computational experiments suggest that the token swap test satisfies the Neyman Pearson condition.

Original languageEnglish (US)
Pages (from-to)269-282
Number of pages14
JournalTheoretical Medicine
Volume7
Issue number3
DOIs
StatePublished - Oct 1 1986

Keywords

  • Computer simulation
  • Hypothesis test
  • Neyman Pearson lemma
  • Token swap test

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Public Health, Environmental and Occupational Health

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