เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| Robust Repeated Measures ANOVA× | Mixed ANOVA× | |
|---|---|---|
| สาขาวิชา | สถิติศาสตร์ | สถิติศาสตร์ |
| ตระกูล | Hypothesis test | Hypothesis test |
| ปีกำเนิด≠ | 1990s–2000s | 1925 |
| ผู้ริเริ่ม≠ | Rand R. Wilcox | R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation |
| ประเภท≠ | Robust parametric mean comparison | Parametric factorial ANOVA |
| แหล่งต้นตำรับ≠ | 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 |
| ชื่อเรียกอื่น | 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) |
| ที่เกี่ยวข้อง | 6 | 6 |
| สรุป≠ | 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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