Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Ανάλυση Λανθανουσών Κλάσεων (LCA)× | Διερευνητική Ανάλυση Παραγόντων (EFA)× | |
|---|---|---|
| Πεδίο | Στατιστική | Στατιστική |
| Οικογένεια | Latent structure | Latent structure |
| Έτος προέλευσης≠ | 1950 | — |
| Δημιουργός≠ | Paul F. Lazarsfeld | — |
| Τύπος≠ | Latent variable / probabilistic clustering | Latent variable / dimension reduction |
| Θεμελιώδης πηγή≠ | Hagenaars, J. A. & McCutcheon, A. L. (Eds.) (2002). Applied Latent Class Analysis. Cambridge University Press. ISBN: 978-0521594516 | 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 ↗ |
| Εναλλακτικές ονομασίες | Gizil Sınıf Analizi (LCA), latent class model, latent structure analysis | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Συναφείς≠ | 3 | 4 |
| Σύνοψη≠ | Latent class analysis is a probabilistic model-based clustering technique that identifies unobserved subgroups — latent classes — within a population on the basis of patterns of categorical, binary, or ordinal indicator responses. Originating in sociological measurement theory with Lazarsfeld's latent structure work around 1950 and formalised computationally by Goodman in the 1970s, it is widely used in the social, health, and behavioural sciences to reveal hidden population heterogeneity. | 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. |
| ScholarGateΣύνολο δεδομένων ↗ |
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