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Our correct use of ANCOVA yields acceptable results

Published online by Cambridge University Press:  02 February 2007

KAARIN J. ANSTEY
Affiliation:
Centre for Mental Health Research, Australian National University, Canberra, Australia
AGUS SALIM
Affiliation:
Centre for Mental Health Research, Australian National University, Canberra, Australia
STEPHEN R. LORD
Affiliation:
Prince of Wales Medical Research Institute, Sydney, Australia
MICHAEL HENNESSY
Affiliation:
School of Ophthalmology, University of New South Wales, Sydney, Australia
PAUL MITCHELL
Affiliation:
School of Ophthalmology, University of Sydney, Sydney, Australia
KATHERINE MILL
Affiliation:
Prince of Wales Medical Research Institute, Sydney, Australia
CHWEE VON SANDEN
Affiliation:
Centre for Mental Health Research, Australian National University, Canberra, Australia

Extract

Gilmore (2007) argues that the use of ANCOVA in Anstey et al. (2006) is invalid. Based on quotes in Winer (1971), he claims that covariates cannot be used to adjust interaction terms involving within-subject variables. Because the within-subject variable in Anstey et al. (2006) is time, he concludes that the results involving Time × Group interaction coefficient are invalid and consequently all analyses need to be re-done.

Type
LETTERS TO THE EDITOR
Copyright
© 2007 The International Neuropsychological Society

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References

REFERENCES

Anstey, K.J., Lord, S.R., Hennessy, M., Mitchell, P., Mill, K., & von Sanden, C. (2006). The effect of cataract surgery on neuropsychological test performance: A randomized controlled trial. Journal of the International Neuropsychological Society, 12, 632639.Google Scholar
Gilmore, G. (2007, this issue). Inappropriate use of covariate analysis renders meaningless results. Journal of the International Neuropsychological Society, 13, 370.Google Scholar
SPSS Knowledgebase (2001, December 10). Resolution 22133: Repeated measures with constant covariates in GLM. Message archived at http://support.spss.com/tech.
Winer, B.J. (1971). Statistical principles in experimental design (2nd ed.). New York: McGraw-Hill.