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	क्रमिक लॉजिस्टिक प्रतिगमन (आनुपातिक ऑड्स मॉडल)	अव्यक्त वर्ग विश्लेषण (Latent Class Analysis - LCA)
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Latent structure
उद्भव वर्ष	2010	1950s–1968
प्रवर्तक	Agresti (textbook treatment); proportional odds model	Paul F. Lazarsfeld
प्रकार	Ordinal logistic regression	Latent variable / person-centered classification
मौलिक स्रोत	Agresti, A. (2010). Analysis of Ordinal Categorical Data (2nd ed.). Wiley.	Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231.
उपनाम	proportional odds model, ordered logit, ordinal logistic regression, Ordinal Regresyon (Proportional Odds)	LCA, latent class model, latent categorical analysis, finite mixture of multinomials
संबंधित	5	6
सारांश	Ordinal logistic regression models an ordered categorical outcome — such as a Likert rating, a satisfaction level, or an education tier — as a function of predictors. It is the ordinal extension of logistic regression, developed in standard treatments such as Agresti's Analysis of Ordinal Categorical Data (2010), and in its most common form it is the proportional odds model.	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.