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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24206

Title: Modeling Through Latent Variables
Authors: Verbeke, Geert
Molenberghs, Geert
Issue Date: 2017
Publisher: ANNUAL REVIEWS
Citation: ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 4, 4, p. 267-282
Abstract: In this review, we give a general overview of latent variable models. We introduce the general model and discuss various inferential approaches. Afterward, we present several commonly applied special cases, including mixture or latent class models, as well as mixed models. We apply many of these models to a single data set with simple structure, allowing for easy comparison of the results. This allows us to discuss advantages and disadvantages of the various approaches, but also to illustrate several problems inherently linked to models incorporating latent structures. Finally, we touch on model extensions and applications and highlight several issues often ignored when applying latent variable models.
Notes: [Verbeke, Geert; Molenberghs, Geert] Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat, B-3000 Leuven, Belgium. [Verbeke, Geert; Molenberghs, Geert] Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Hasselt, Belgium.
URI: http://hdl.handle.net/1942/24206
DOI: 10.1146/annurev-statistics-060116-054017
ISI #: 000398070800013
ISBN: 9780824336042
ISSN: 2326-8298
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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