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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Bibliographic Details
Published in:	Psychometrika Vol. 89; no. 2; pp. 626 - 657
Main Authors:	Chen, Ling, Gu, Yuqi
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.06.2024 Springer Nature B.V
Subjects:	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
Online Access:	Get full text
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