方法对比
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| 纵向假设检验研究× | 重复测量方差分析× | |
|---|---|---|
| 领域≠ | 研究设计 | 统计学 |
| 方法族≠ | Process / pipeline | Hypothesis test |
| 起源年份≠ | Consolidated as a formal design framework in the 1960s–1980s | 1992 |
| 提出者≠ | Synthesized from longitudinal design traditions (Lazarsfeld, 1940s) and classical hypothesis testing (Fisher, Neyman-Pearson, 1920s–1930s) | Girden (textbook treatment); Field (2013) |
| 类型≠ | Quantitative longitudinal research design | Parametric within-subjects mean comparison |
| 开创性文献≠ | Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford University Press. ISBN: 978-0195152968 | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185 |
| 别名 | longitudinal confirmatory study, repeated-measures hypothesis testing, prospective hypothesis testing, longitudinal inferential research | within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA |
| 相关≠ | 5 | 4 |
| 摘要≠ | Longitudinal hypothesis testing research combines a longitudinal design — measuring the same units repeatedly over time — with formal null-hypothesis significance testing to determine whether observed changes exceed what chance alone can explain. It is widely used in education, medicine, psychology, and social science to test directional predictions about change, stability, or group differences that emerge over a defined time span. | 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). |
| ScholarGate数据集 ↗ |
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