Modified p-values for one-sided testing in restricted parameter spaces

Hsiuying Wang*

*Corresponding author for this work

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

For testing the mean of a normal distribution, the p-value, derived from the uniformly most powerful test, is usually used as evidence against the null hypothesis. However, the p-value only depends on the hypothesis assumption, but not on the bounds of the parameter space. When the parameter space is restricted, the information of the restriction will not be sufficiently utilized if we still use the usual p-value as evidence against the null hypothesis. In this paper, a modified p-value, based on the bounds of the parameter space for one-sided hypothesis testing, is proposed. Theoretical and simulation studies show that the modified p-value has better performance than the usual p-value from theoretical and simulation studies.

Original languageEnglish
Pages (from-to)625-631
Number of pages7
JournalStatistics and Probability Letters
Volume77
Issue number6
DOIs
StatePublished - 15 Mar 2007

Keywords

  • Bayes estimators
  • Hypothesis testing
  • p-value
  • Restricted parameter space

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