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| Latent Profile Analysis (LPA)× | Konfirmerande faktoranalys (CFA)× | Latent Class Analysis (LCA)× | |
|---|---|---|---|
| Ämnesområde≠ | Psykometri | Statistik | Statistik |
| Familj | Latent structure | Latent structure | Latent structure |
| Ursprungsår≠ | 2010 | 1969 | 1950s–1968 |
| Upphovsperson≠ | Lazarsfeld & Henry; Collins & Lanza | Karl Jöreskog | Paul F. Lazarsfeld |
| Typ≠ | Person-centered finite mixture model | Confirmatory latent variable model | Latent variable / person-centered classification |
| Ursprungskälla≠ | Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis. Wiley. ISBN: 978-0-470-22839-7 | Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363 | Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231. DOI ↗ |
| Alias≠ | Continuous Latent Class Analysis, Gaussian Profile Mixture Model, Person-Centered Cluster Analysis, Gizil Profil Analizi | Doğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model | LCA, latent class model, latent categorical analysis, finite mixture of multinomials |
| Närliggande≠ | 2 | 4 | 6 |
| Sammanfattning≠ | Latent Profile Analysis (LPA) is a person-centered finite mixture modeling technique that identifies unobserved subgroups — called profiles — within a population based on patterns of scores across multiple continuous indicators. Rooted in Lazarsfeld and Henry's latent structure tradition and formally synthesized for applied behavioral research by Collins and Lanza (2010), LPA assumes that observed heterogeneity in continuous data arises from a discrete number of latent classes, each characterized by a unique multivariate mean profile. | 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. | Latent class analysis identifies unobserved subgroups — latent classes — within a population by finding patterns of responses across a set of categorical observed indicators. It is the categorical-variable counterpart of cluster analysis, but grounded in an explicit probabilistic model, and is widely used in social, health, and behavioral sciences to discover typologies in survey or diagnostic data. |
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