Methoden vergleichen

	Latent Transition Analysis in Education	Latente Klassenanalyse (LCA)
Fachgebiet	Education	Statistik
Familie	Latent structure	Latent structure
Entstehungsjahr	2010	1950s–1968
Urheber	Latent variable methodology (Collins & Wugalter; Collins & Lanza)	Paul F. Lazarsfeld
Typ	Longitudinal latent class model for movement between qualitative learner states	Latent variable / person-centered classification
Wegweisende Quelle	Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences. Wiley. ISBN: 9780470228395	Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231.
Aliasnamen	Educational LTA, Latent Markov Modeling of Learning, Stage-Sequential Latent Class Modeling, Latent Transition Modeling	LCA, latent class model, latent categorical analysis, finite mixture of multinomials
Verwandt	4	6
Zusammenfassung	Latent transition analysis (LTA) is a longitudinal extension of latent class analysis that models how individuals move between qualitatively distinct, unobserved categories over time. In education it represents students as belonging to learner profiles or developmental stages — for example, types of motivation, reading-strategy profiles, or mastery stages — and estimates the probabilities of transitioning from one profile to another between time points. It answers not only how many kinds of learners there are, but how learners change type as instruction and development unfold.	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.