方法对比
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| 层级探索性定量研究× | 探索性因子分析（EFA）× | |
|---|---|---|
| 领域≠ | 研究设计 | 统计学 |
| 方法族≠ | Process / pipeline | Latent structure |
| 起源年份≠ | mid-20th century onward | — |
| 提出者≠ | Developed from survey research traditions (Kish, 1965; Babbie, 1990s) | — |
| 类型≠ | Quantitative observational and survey design | Latent variable / dimension reduction |
| 开创性文献≠ | Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage Publications. ISBN: 978-1452226101 | Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗ |
| 别名≠ | stratified exploratory survey design, hierarchical survey research, multilevel exploratory quantitative design, hierarchical descriptive-quantitative design | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| 相关≠ | 2 | 4 |
| 摘要≠ | Hierarchical exploratory quantitative research is a survey and observational design that structures both sampling and analysis across nested population levels — such as students within classrooms within schools — to explore patterns, distributions, and relationships in numerical data without a pre-specified directional hypothesis. It is oriented toward discovery and description rather than confirmation, making it appropriate early in a research programme when the phenomenon is not yet well-mapped. | Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance. |
| ScholarGate数据集 ↗ |
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