An Introduction to Latent Class Analysis: Methods and Applications (Behaviormetrics: Quantitative Approaches to Human Behavior, Band 14) - Softcover

Eshima, Nobuoki

Softcover

ISBN 10: 9811909741 ISBN 13: 9789811909740

Verlag: Springer, 2023

Inhaltsangabe

This book provides methods and applications of latent class analysis, and the following topics are taken up in the focus of discussion: basic latent structure models in a framework of generalized linear models, exploratory latent class analysis, latent class analysis with ordered latent classes, a latent class model approach for analyzing learning structures, the latent Markov analysis for longitudinal data, and path analysis with latent class models. The maximum likelihood estimation procedures for latent class models are constructed via the expectation–maximization (EM) algorithm, and along with it, latent profile and latent trait models are also treated. Entropy-based discussions for latent class models are given as advanced approaches, for example, comparison of latent classes in a latent class cluster model, assessing latent class models, path analysis, and so on. In observing human behaviors and responses to various stimuli and test items, it is valid to assume they are dominated by certain factors. This book plays a significant role in introducing latent structure analysis to not only young researchers and students studying behavioral sciences, but also to those investigating other fields of scientific research. 

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Über die Autorin bzw. den Autor

Nobuoki Eshima was born in Fukuoka, Japan, in 1957. He was received B.Sc. and D.Sc. degrees in Mathematics from Kyushu University, Fukuoka, Japan, in 1980 and 1993, respectively. In 1993, he joined Department of Statistics, Faculty of General Education, Nagasaki University, as Associate Professor. In 1996, he joined Department of Medical Information Analysis, Faculty of Medicine, Oita Medical University, as Professor. In 2016, he joined Center for Educational Outreach and Admissions, Kyoto University, as Professor. In 2021, he was granted the title of Emeritus Professor of Oita University, and from 2021, he is Guest Professor of Faculty of Medicine, Kurume University.

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This book provides methods and applications of latent class analysis, and the following topics are taken up in the focus of discussion: basic latent structure models in a framework of generalized linear models, exploratory latent class analysis, latent class analysis with ordered latent classes, a latent class model approach for analyzing learning structures, the latent Markov analysis for longitudinal data, and path analysis with latent class models. The maximum likelihood estimation procedures for latent class models are constructed via the expectation–maximization (EM) algorithm, and along with it, latent profile and latent trait models are also treated. Entropy-based discussions for latent class models are given as advanced approaches, for example, comparison of latent classes in a latent class cluster model, assessing latent class models, path analysis, and so on. In observing human behaviors and responses to various stimuli and test items, it is valid to assume they are dominatedby certain factors. This book plays a significant role in introducing latent structure analysis to not only young researchers and students studying behavioral sciences, but also to those investigating other fields of scientific research. 

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2023
• Sprache: Englisch
• ISBN 10: 9811909741
• ISBN 13: 9789811909740
• Einband: Taschenbuch
• Auflage: 1
• Anzahl der Seiten: 204
• Kontakt zum Hersteller: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Deutschland