Huynh Feldt Correction
- Adjustment applied in repeated-measures analyses when sphericity is violated.
- Modifies degrees of freedom to make ANOVA results more accurate.
- Used to obtain more reliable conclusions about changes across repeated measurements.
Definition
Section titled “Definition”Huynh-Feldt correction is a statistical technique used to adjust the degrees of freedom in repeated measures designs. This correction is applied when the assumptions of sphericity, which is the assumption that the variances of the differences between all possible pairs of repeated measures are equal, are not met.
Explanation
Section titled “Explanation”When repeated measurements are taken from the same participants, repeated measures ANOVA assumes sphericity — equal variances of the differences between every pair of measurement occasions. If that assumption does not hold, standard F tests can be biased. The Huynh-Feldt correction adjusts the degrees of freedom used in the ANOVA test to account for the violation of sphericity, which can improve the accuracy of the resulting statistical conclusions.
Examples
Section titled “Examples”Anxiety treatment study
Section titled “Anxiety treatment study”Researchers measure participants’ anxiety levels at three different time points: before the treatment, immediately after the treatment, and one week after the treatment. A repeated measures ANOVA compares the means of the three time points. If the assumption of sphericity is not met, the Huynh-Feldt correction can be applied to adjust the degrees of freedom and improve the accuracy of the ANOVA results.
Cognitive training and memory study
Section titled “Cognitive training and memory study”Researchers measure older adults’ memory performance at three different time points: before the training program, immediately after the training program, and one month after the training program. A repeated measures ANOVA compares the means of the three time points. If the assumption of sphericity is not met, the Huynh-Feldt correction can be applied to adjust the degrees of freedom and improve the accuracy of the ANOVA results.
Use cases
Section titled “Use cases”- Applied in repeated measures ANOVA to adjust degrees of freedom when sphericity is violated, with the goal of improving the accuracy of ANOVA results and producing more reliable conclusions about treatment or intervention effects.
Related terms
Section titled “Related terms”- Sphericity
- Repeated measures ANOVA
- Degrees of freedom