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| Bayesian Two-Way ANOVA× | Zwei-Wege-Varianzanalyse (Two-Way ANOVA)× | |
|---|---|---|
| Fachgebiet | Statistik | Statistik |
| Familie | Hypothesis test | Hypothesis test |
| Entstehungsjahr≠ | 1961 (foundations); 2012 (default Bayes factor formulation) | 1925 |
| Urheber≠ | Harold Jeffreys (foundational); modern default-prior form by Jeffrey N. Rouder et al. | Ronald A. Fisher |
| Typ≠ | Bayesian hypothesis test | Parametric factorial mean comparison |
| Wegweisende Quelle≠ | Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356–374. DOI ↗ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 |
| Aliasnamen≠ | Bayesian factorial ANOVA, Bayes factor two-way ANOVA, Bayesian 2×k ANOVA, Bayesian two-factor ANOVA | factorial ANOVA, two-factor ANOVA, İki Yönlü ANOVA |
| Verwandt≠ | 4 | 6 |
| Zusammenfassung≠ | Bayesian two-way ANOVA extends the classical two-way analysis of variance by replacing p-values with Bayes factors and posterior distributions. It quantifies evidence for or against main effects and their interaction using prior-weighted model comparison, yielding conclusions that are directly interpretable in probabilistic terms rather than relying on a fixed significance threshold. | Two-Way ANOVA is a parametric hypothesis test that simultaneously examines the main effects of two independent categorical factors and their interaction effect on a single continuous dependent variable. The technique was developed within the broader framework of the analysis of variance established by Ronald A. Fisher in 1925 and remains the standard approach whenever an experiment or survey includes exactly two between-subjects factors. |
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