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| Multivariate explorative quantitative Forschung× | Bestätigende Forschung – Theorieprüfendes quantitatives Design× | |
|---|---|---|
| Fachgebiet | Forschungsdesign | Forschungsdesign |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1930s–1960s (foundational multivariate methods); codified in research design literature from the 1980s onward | 1934 (Popper); widely adopted in social sciences from 1960s onward |
| Urheber≠ | 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 |
| Typ | Quantitative research design | Quantitative research design |
| Wegweisende Quelle≠ | 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 |
| Aliasnamen | multivariate exploratory design, exploratory multivariate analysis, multivariate data exploration, MEQ research | hypothesis-testing research, deductive research, theory-testing research, confirmatory study |
| Verwandt≠ | 5 | 4 |
| Zusammenfassung≠ | 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. |
| ScholarGateDatensatz ↗ |
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