Mixed-design ANOVA

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In this ANOVA model (also known as Split-plot ANOVA (SPANOVA)), one tests for differences between two or more independent groups whilst subjecting participants to repeated measures. Thus, one factor is a between subjects variable and the other is within subjects variable.

[edit] Assumption testing

One continuous DV, one or more categorical within-subject IVs, and one or more categorical between-subject IVs e.g., Pulse rate (DV), Time (pre and post exercise) within-subject IV, and Gender as a between-subject IV.
Sample size - ideally, at least 20 cases per cell
Distribution of the DV for each cell is normal
Independence: Each participants' responses are sampled independently from each other participants' responses (e.g., this can be satisfied by random selection).
Homogeneity of variance: Cells have similar variances.
Sphericity: Population variances of the repeated measurements are equal and the population correlations among all pairs of measures are equal. Tested by Mauchley's or Box's M. Violation increases Type I error rate. If violated, interpret adjusted results (e.g., Greenhouse-Geisser).
See also these slides