Sizing fixed effects for computing power in experimental designs

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Power tells us the probability of rejecting the null hypothesis for an effect of a given size and helps us select an appropriate design prior to running the experiment. The key to computing power for an effect is determining the size of the effect. We describe a general approach for sizing effects that covers a wide variety of designs including factorials with categorical levels, response surfaces, mixtures and crossed designs.

Original languageEnglish (US)
Pages (from-to)291-306
Number of pages16
JournalQuality and Reliability Engineering International
Volume17
Issue number4
DOIs
StatePublished - Jul 1 2001

Keywords

  • Factorials
  • Fixed effects
  • Mixtures
  • Power
  • Response surfaces
  • Type 2 error

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