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03 February 2026

In this presentation, we evaluate both Type I error rates and powers of the 13 tests investigated in Pham et al. (2020) spanning ANOVA-based tests, structured means modeling (SMM), and mixed-effects models—under diverse conditions, including (un)equal variances, (non-)normal distributions, and (un)balanced designs. Two additional mixed-effects models (homogeneous-variance mixed-effects model and adaptive mixed-effects model) are introduced and assessed alongside the 13 tests. We also consider the Kenward-Roger approximation of degrees of freedom for the 3 mixed-effects models, which generally offers more reliable type I error rate than the Satterthwaite approximation. Some recommendations about analysis for data from single-factor experiments will finally be given.

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