方法对比
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| 交叉析因实验× | 重复测量方差分析× | |
|---|---|---|
| 领域≠ | 实验设计 | 统计学 |
| 方法族≠ | Process / pipeline | Hypothesis test |
| 起源年份≠ | 1920s–1960s (synthesis of factorial and crossover traditions) | 1992 |
| 提出者≠ | R. A. Fisher (factorial principles, 1920s); crossover integration developed in biostatistics through mid-20th century | Girden (textbook treatment); Field (2013) |
| 类型≠ | Experimental design | Parametric within-subjects mean comparison |
| 开创性文献≠ | Jones, B., & Kenward, M. G. (2014). Design and Analysis of Cross-Over Trials (3rd ed.). Chapman and Hall/CRC. ISBN: 978-1439861424 | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185 |
| 别名 | within-subject factorial design, repeated-measures factorial experiment, factorial crossover trial, crossover factorial trial | within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA |
| 相关≠ | 5 | 4 |
| 摘要≠ | A crossover factorial experiment combines two powerful design principles: factorial structure, which studies multiple factors and their interactions simultaneously, and crossover structure, in which each participant receives more than one treatment combination across sequential periods. By serving as their own control, participants reduce between-subject variability, improving statistical power while also revealing how different factor levels interact within the same individual. | Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013). |
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