A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses

Grade of membership (GoM) models are popular individual-level mixture models for multivariate categorical data. GoM allows each subject to have mixed memberships in multiple extreme latent profiles. Therefore, GoM models have a richer modeling capacity than latent class models that restrict each sub...

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Vydané v:	Psychometrika Ročník 89; číslo 2; s. 626 - 657
Hlavní autori:	Chen, Ling, Gu, Yuqi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.06.2024 Springer Nature B.V
Predmet:	Algorithms Assessment Bayes Theorem Bayesian analysis Behavioral Science and Psychology Computer Simulation Decomposition Efficiency Expectation Humanities Humans Law Mathematical models Memberships Models, Statistical Personality Measures Psychology Psychometrics Psychometrics - methods Quantitative psychology Simulation Statistical Theory and Methods Statistics for Social Sciences Testing and Evaluation Theory & Methods Variables spectral method successive projection algorithm grade of membership model identifiability latent variable model singular value decomposition mixed membership model
ISSN:	0033-3123, 1860-0980, 1860-0980
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