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.Â
General
Imprint: |
Springer Verlag, Singapore
|
Country of origin: |
Singapore |
Series: |
Behaviormetrics: Quantitative Approaches to Human Behavior, 14 |
Release date: |
April 2023 |
First published: |
2022 |
Authors: |
Nobuoki Eshima
|
Dimensions: |
235 x 155mm (L x W) |
Pages: |
190 |
Edition: |
1st ed. 2022 |
ISBN-13: |
978-981-19-0974-0 |
Categories: |
Books
|
LSN: |
981-19-0974-1 |
Barcode: |
9789811909740 |
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