方法对比

	多元探索性定量研究	确认性研究
领域	研究设计	研究设计
方法族	Process / pipeline	Process / pipeline
起源年份	1930s–1960s (foundational multivariate methods); codified in research design literature from the 1980s onward	1934 (Popper); widely adopted in social sciences from 1960s onward
提出者	Hair, Tabachnick, and colleagues (canonical synthesis); roots in Fisher, Hotelling, and Thurstone (early 20th century)	Karl Popper (falsificationism); formalized in behavioral sciences by Paul Meehl and others
类型	Quantitative research design	Quantitative research design
开创性文献	Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540	Popper, K. R. (1959). The Logic of Scientific Discovery. Hutchinson. ISBN: 978-0415278447
别名	multivariate exploratory design, exploratory multivariate analysis, multivariate data exploration, MEQ research	hypothesis-testing research, deductive research, theory-testing research, confirmatory study
相关	5	4
摘要	Multivariate exploratory quantitative research is a design in which researchers simultaneously examine multiple quantitative variables without imposing a predetermined structural model, using techniques such as exploratory factor analysis, cluster analysis, or principal component analysis to detect latent patterns, natural groupings, or underlying dimensions in the data. The goal is discovery and pattern recognition rather than hypothesis confirmation.	Confirmatory research is a deductive quantitative design in which the researcher specifies hypotheses derived from existing theory before data collection, then tests whether the data support or refute those hypotheses. Unlike exploratory approaches that generate ideas from data, confirmatory research begins with an established theoretical framework, pre-registers predictions, and applies statistical tests to evaluate those predictions against empirical evidence. It is the backbone of hypothesis-driven social, behavioral, and health science inquiry.