手法を比較

	階層的探索的量的研究	因子分析（EFA）
分野	研究デザイン	統計学
系統	Process / pipeline	Latent structure
提唱年	mid-20th century onward	—
提唱者	Developed from survey research traditions (Kish, 1965; Babbie, 1990s)	—
種類	Quantitative observational and survey design	Latent variable / dimension reduction
原典	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.
別名	stratified exploratory survey design, hierarchical survey research, multilevel exploratory quantitative design, hierarchical descriptive-quantitative design	common factor analysis, açımlayıcı faktör analizi, factor analysis
関連	2	4
概要	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.