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| 강건 반복 측정 분산 분석 (Robust Repeated Measures ANOVA)× | 혼합 분산 분석× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1990s–2000s | 1925 |
| 창시자≠ | Rand R. Wilcox | R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation |
| 유형≠ | Robust parametric mean comparison | Parametric factorial ANOVA |
| 원전≠ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 | Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE. ISBN: 978-1526419521 |
| 별칭 | robust within-subjects ANOVA, trimmed-mean repeated measures ANOVA, robust RM-ANOVA, heteroscedastic repeated measures ANOVA | split-plot ANOVA, mixed-design ANOVA, between-within ANOVA, Karma ANOVA (Mixed ANOVA — Gruplar Arası × Tekrarlı) |
| 관련 | 6 | 6 |
| 요약≠ | Robust repeated measures ANOVA tests whether population trimmed means differ across three or more repeated conditions or time points measured on the same subjects. By replacing ordinary means with 20% trimmed means and replacing variances with Winsorized estimates, it maintains acceptable Type I error and power when data are non-normal, skewed, or contain outliers — conditions under which classical repeated measures ANOVA routinely breaks down. | 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. |
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