השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| מחקר כמותי רב-משתני חקרני× | ניתוח גורמים גישוש (EFA)× | |
|---|---|---|
| תחום≠ | תכנון מחקר | סטטיסטיקה |
| משפחה≠ | Process / pipeline | Latent structure |
| שנת המקור≠ | 1930s–1960s (foundational multivariate methods); codified in research design literature from the 1980s onward | — |
| הוגה השיטה≠ | Hair, Tabachnick, and colleagues (canonical synthesis); roots in Fisher, Hotelling, and Thurstone (early 20th century) | — |
| סוג≠ | Quantitative research design | Latent variable / dimension reduction |
| מקור מכונן≠ | Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540 | 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 ↗ |
| כינויים≠ | multivariate exploratory design, exploratory multivariate analysis, multivariate data exploration, MEQ research | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| קשורות≠ | 5 | 4 |
| תקציר≠ | 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. | 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. |
| ScholarGateמערך נתונים ↗ |
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