Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Analiza factorială× | Analiza de regresie multiplă× | |
|---|---|---|
| Domeniu | Statistică pentru cercetare | Statistică pentru cercetare |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1931 | 1801 |
| Autorul original≠ | Louis Leon Thurstone | Carl Friedrich Gauss |
| Tip | Method | Method |
| Sursa seminală≠ | Thurstone, L. L. (1947). Multiple Factor Analysis. University of Chicago Press. DOI ↗ | Draper, N. R., & Smith, H. (1966). Applied Regression Analysis. John Wiley & Sons. link ↗ |
| Denumiri alternative | EFA, CFA, latent variable modeling | MLR, multivariate regression, linear regression |
| Înrudite≠ | 3 | 4 |
| Rezumat≠ | Factor analysis is a statistical technique for identifying latent (unobserved) dimensions underlying observed variables, developed by Louis Leon Thurstone in the 1930s and formalized by Jöreskog (1969). Exploratory factor analysis (EFA) discovers unknown factor structure from data; confirmatory factor analysis (CFA) tests hypothesized relationships between observed and latent variables. Essential in psychometrics (test development), organizational research (measuring constructs like leadership style), and biomedicine (identifying disease subtypes), factor analysis reduces dimensionality while revealing conceptual organization in multivariate data. | Multiple regression analysis is a statistical method for modeling the relationship between a continuous dependent variable and two or more independent variables (predictors). Originating from Gauss's early 19th-century work and formalized by Draper and Smith (1966), it estimates linear equations predicting outcomes from multiple predictors while accounting for confounding relationships, making it indispensable in epidemiology, economics, psychology, and clinical research. |
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