Smoothing balanced single-error-term analysis of variance

James S. Hodges, Daniel J. Sargent, Yue Cui, Bradley P. Carlin

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


We present an approach to smoothing balanced, single-error term analysis of variance (ANOVA), descended from Smith, that also allows spatial, temporal, or spatiotemporal smoothing. The approach addresses unreplicated designs, masked contrasts in effects with many degrees of freedom, and subgroup analysis, demonstrated using a study of denture-lining materials. Our approach is Bayesian but can be viewed as a way to generate frequentist procedures. A simulation experiment compares four priors, unsmoothed ANOVA, and dropping nonsignificant interactions. Three priors have advantages when some interactions are absent; dropping nonsignificant interactions has serious flaws. We contrast our approach with the approaches of Nobile-Green and Gelman.

Original languageEnglish (US)
Pages (from-to)12-25
Number of pages14
Issue number1
StatePublished - Feb 2007


  • Bayesian analysis
  • Degrees of freedom
  • Masking
  • Prior distribution
  • Shrinkage
  • Sub-group analysis

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Applied Mathematics


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