Partial replication of small two-level factorial designs

Bradley Jones, Douglas Montgomery

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Replicating runs in designed experiments is good practice. The most important reason to replicate runs is to allow for a model-independent estimate of the error variance. Without the pure error degrees of freedom provided by replicated runs, the error variance will be biased if the fitted model is missing an active effect. This work provides a replication strategy for full-factorial designs having two to four factors. However, our approach is general and could be applied to any factorial experiment.

Original languageEnglish (US)
Pages (from-to)190-195
Number of pages6
JournalQuality Engineering
Issue number2
StatePublished - Apr 3 2017


  • design of experiments
  • factorial
  • power
  • pure error
  • replication

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering


Dive into the research topics of 'Partial replication of small two-level factorial designs'. Together they form a unique fingerprint.

Cite this