Greenhouse–Geisser correction explained
The Greenhouse–Geisser correction
is a statistical method of adjusting for lack of
sphericity in a repeated measures ANOVA. The correction functions as both an estimate of epsilon (sphericity) and a correction for lack of sphericity. The correction was proposed by
Samuel Greenhouse and
Seymour Geisser in 1959.
[1] The Greenhouse–Geisser correction is an estimate of sphericity (
). If sphericity is met, then
. If sphericity is not met, then epsilon will be less than 1 (and the degrees of freedom will be overestimated and the F-value will be inflated).
[2] To correct for this inflation, multiply the Greenhouse–Geisser estimate of epsilon to the degrees of freedom used to calculate the F critical value.
An alternative correction that is believed to be less conservative is the Huynh–Feldt correction (1976). As a general rule of thumb, the Greenhouse–Geisser correction is the preferred correction method when the epsilon estimate is below 0.75. Otherwise, the Huynh–Feldt correction is preferred.[3]
See also
Notes and References
- Greenhouse . S. W. . Geisser . S. . On methods in the analysis ofprofile data . Psychometrika . 1959 . 24 . 95–112.
- Book: Andy Field. Discovering Statistics Using SPSS. 21 January 2009. SAGE Publications. 978-1-84787-906-6. 461.
- Book: J. P. Verma. Repeated Measures Design for Empirical Researchers. 21 August 2015. John Wiley & Sons. 978-1-119-05269-2. 84.
