Сравнение методов

	Латентно-классовый анализ (LCA)	Модель Раша
Область	Статистика	Психометрия
Семейство	Latent structure	Latent structure
Год появления	1950s–1968	1960
Автор метода	Paul F. Lazarsfeld	Georg Rasch
Тип	Latent variable / person-centered classification	Item Response Theory / Latent trait model
Основополагающий источник	Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231.	Rasch, G. (1960). Probabilistic Models for Some Intelligence and Attainment Tests. Danish Institute for Educational Research, Copenhagen.
Другие названия	LCA, latent class model, latent categorical analysis, finite mixture of multinomials	1PL IRT, one-parameter logistic model, Rasch Modeli — 1PL IRT, 1PL model
Связанные	6	6
Сводка	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.	The Rasch model, introduced by Georg Rasch in 1960, is the simplest member of the Item Response Theory (IRT) family. It assigns a single difficulty parameter to each test item and places both item difficulties and person abilities on the same logit scale, enabling direct, sample-independent comparison of items and persons.