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| Байесов фактор анализ× | Конфирматорният факторен анализ (КФА)× | Експлораторният факторен анализ (EFA)× | |
|---|---|---|---|
| Област≠ | Бейсови методи | Статистика | Статистика |
| Семейство≠ | Bayesian methods | Latent structure | Latent structure |
| Година на възникване≠ | 2004 | 1969 | — |
| Създател≠ | Lopes & West (2004) for Bayesian model assessment in factor analysis | Karl Jöreskog | — |
| Тип≠ | Bayesian latent variable model | Confirmatory latent variable model | Latent variable / dimension reduction |
| Основополагащ източник≠ | Lopes, H. F. & West, M. (2004). Bayesian Model Assessment in Factor Analysis. Statistica Sinica, 14(1), 41–67. link ↗ | Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363 | 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 ↗ |
| Други названия≠ | Bayesian EFA, Bayesian CFA, Bayesçi Faktör Analizi, probabilistic factor analysis | Doğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Свързани≠ | 7 | 4 | 4 |
| Резюме≠ | Bayesian Factor Analysis is a probabilistic latent-variable method that places prior distributions on the factor loading matrix and the residual variances, then infers a full posterior over these parameters from the observed data. Developed prominently in the Bayesian framework by Lopes and West (2004), it extends classical exploratory and confirmatory factor analysis by quantifying uncertainty in every estimated loading rather than reporting single point estimates. | Confirmatory factor analysis tests whether a researcher-specified factor structure fits the observed data. Formalised by Karl Jöreskog in 1969, it is the measurement-model step within structural equation modelling and is the standard tool for validating the factorial structure of scales and questionnaires before comparing groups or estimating latent relationships. | 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. |
| ScholarGateНабор от данни ↗ |
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