A study of type ii and type iii power for testing hypotheses from unbalanced factorial designs

J.D. Lewsey, W.P. Gardiner, G. Gettinby

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Methods for analysing unbalanced factorial designs are well documented when there is at least one observation for all treatment combinations. The Type II and Type III methods, as they have become known, are the methods of choice for hypothesis testing purposes, but there is no consensus about which is more suitable. The aim of this paper is to assess how the deterioration of the balanced structure in a given designinfluences Type II and Type III power, both when negligible/ insignificant interactions and no interactions exist. A simulation study was set up using 726 unbalanced designs which stem from a 23 factorial design with three replicates per cell. The sampling scheme was chosen so that the interaction effect was negligible and associated with low power. A separate study investigated a 20% random sample of the unbalanced designs identified above, but fixing the interaction effect to be zero. The results from the simulation study showed that, regardless of how many observations were lost from the balanced design, the median Type II power was greater and the inter-quartile range of Type II power wider than the corresponding values for Type III power. This is an important message for practitioners, namely that the Type II method is, on average, more powerful than the Type III method but is also more influenced by cell patterning than the Type III method. There was also some evidence to suggest that up to a certain point, which is particular to the factorial design set-up, as more observations are lost the Type II method will be increasingly more powerful than the Type III method.
LanguageEnglish
Pages597-609
Number of pages12
JournalCommunications in Statistics - Simulation and Computation
Volume30
Issue number3
DOIs
Publication statusPublished - 2001

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Unbalanced Designs
Testing Hypotheses
Factorial Design
Testing
Interquartile range
Balanced Design
Patterning
Deterioration
Interaction
Sampling
Cell
Zero
Observation
Simulation

Keywords

  • unbalanced factorial designs

Cite this

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abstract = "Methods for analysing unbalanced factorial designs are well documented when there is at least one observation for all treatment combinations. The Type II and Type III methods, as they have become known, are the methods of choice for hypothesis testing purposes, but there is no consensus about which is more suitable. The aim of this paper is to assess how the deterioration of the balanced structure in a given designinfluences Type II and Type III power, both when negligible/ insignificant interactions and no interactions exist. A simulation study was set up using 726 unbalanced designs which stem from a 23 factorial design with three replicates per cell. The sampling scheme was chosen so that the interaction effect was negligible and associated with low power. A separate study investigated a 20{\%} random sample of the unbalanced designs identified above, but fixing the interaction effect to be zero. The results from the simulation study showed that, regardless of how many observations were lost from the balanced design, the median Type II power was greater and the inter-quartile range of Type II power wider than the corresponding values for Type III power. This is an important message for practitioners, namely that the Type II method is, on average, more powerful than the Type III method but is also more influenced by cell patterning than the Type III method. There was also some evidence to suggest that up to a certain point, which is particular to the factorial design set-up, as more observations are lost the Type II method will be increasingly more powerful than the Type III method.",
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A study of type ii and type iii power for testing hypotheses from unbalanced factorial designs. / Lewsey, J.D.; Gardiner, W.P.; Gettinby, G.

In: Communications in Statistics - Simulation and Computation, Vol. 30, No. 3, 2001, p. 597-609.

Research output: Contribution to journalArticle

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