Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| ANOVA mixte× | Test t pour échantillons appariés× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Hypothesis test | Hypothesis test |
| Année d'origine≠ | 1925 | 1908 |
| Auteur d'origine≠ | R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation | Student (W. S. Gosset) |
| Type≠ | Parametric factorial ANOVA | Parametric mean comparison (paired) |
| Source fondatrice≠ | Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE. ISBN: 978-1526419521 | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE. ISBN: 978-1446249185 |
| Alias | split-plot ANOVA, mixed-design ANOVA, between-within ANOVA, Karma ANOVA (Mixed ANOVA — Gruplar Arası × Tekrarlı) | dependent samples t-test, repeated measures t-test, matched-pairs t-test, eşleştirilmiş örneklem t-testi |
| Apparentées≠ | 6 | 4 |
| Résumé≠ | Mixed ANOVA is a parametric factorial analysis of variance that simultaneously examines at least one between-subjects factor and at least one within-subjects (repeated-measures) factor. Rooted in R. A. Fisher's ANOVA framework formalised in 1925, it is the standard method for experimental and longitudinal designs in which different groups are each measured across multiple time points or conditions. | The paired samples t-test is a parametric hypothesis test that compares two measurements taken on the same subjects — such as a before and after reading — to decide whether the average change differs from zero. It rests on the t-distribution introduced by Student (W. S. Gosset) in 1908 and works on the within-subject difference scores rather than the raw measurements. |
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