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001445879 001__ 1445879
001445879 003__ OCoLC
001445879 005__ 20230310003855.0
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001445879 020__ $$a9789811909726$$q(electronic bk.)
001445879 020__ $$a9811909725$$q(electronic bk.)
001445879 020__ $$z9789811909719
001445879 020__ $$z9811909717
001445879 0247_ $$a10.1007/978-981-19-0972-6$$2doi
001445879 035__ $$aSP(OCoLC)1310619864
001445879 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dEBLCP$$dOCLCO$$dOCLCF$$dN$T$$dSFB$$dUKAHL$$dOCLCQ
001445879 049__ $$aISEA
001445879 050_4 $$aQA278.6$$b.E75 2022
001445879 08204 $$a519.5/35$$223
001445879 1001_ $$aEshima, Nobuoki,$$eauthor.
001445879 24513 $$aAn introduction to latent class analysis :$$bmethods and applications /$$cNobuoki Eshima.
001445879 264_1 $$aSingapore :$$bSpringer,$$c[2022]
001445879 264_4 $$c©2022
001445879 300__ $$a1 online resource :$$billustrations (some color).
001445879 336__ $$atext$$btxt$$2rdacontent
001445879 337__ $$acomputer$$bc$$2rdamedia
001445879 338__ $$aonline resource$$bcr$$2rdacarrier
001445879 4901_ $$aBehaviormetrics - quantitative approaches to human behavior ;$$vvolume 14
001445879 504__ $$aIncludes bibliographical references.
001445879 5050_ $$aOverview of Basic Latent Structure Models -- Latent Class Cluster Analysis -- Latent Class Analysis with Ordered Latent Classes -- Latent Class Analysis with Latent Binary Variables: Application for Analyzing Learning Structures -- The Latent Markov Chain Model -- Mixed Latent Markov Chain Models -- Path Analysis in Latent Class Models.
001445879 506__ $$aAccess limited to authorized users.
001445879 520__ $$aThis book provides methods and applications of latent class analysis, and the following topics are taken up in the focus of discussion: basic latent structure models in a framework of generalized linear models, exploratory latent class analysis, latent class analysis with ordered latent classes, a latent class model approach for analyzing learning structures, the latent Markov analysis for longitudinal data, and path analysis with latent class models. The maximum likelihood estimation procedures for latent class models are constructed via the expectationmaximization (EM) algorithm, and along with it, latent profile and latent trait models are also treated. Entropy-based discussions for latent class models are given as advanced approaches, for example, comparison of latent classes in a latent class cluster model, assessing latent class models, path analysis, and so on. In observing human behaviors and responses to various stimuli and test items, it is valid to assume they are dominated by certain factors. This book plays a significant role in introducing latent structure analysis to not only young researchers and students studying behavioral sciences, but also to those investigating other fields of scientific research. .
001445879 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 13, 2022).
001445879 650_0 $$aLatent structure analysis.
001445879 650_0 $$aLatent variables.
001445879 650_0 $$aHuman behavior$$xResearch$$xMethodology.
001445879 650_6 $$aAnalyse de structure latente.
001445879 650_6 $$aVariables latentes.
001445879 650_6 $$aComportement humain$$xRecherche$$xMéthodologie.
001445879 655_7 $$aLlibres electrònics.$$2thub
001445879 655_0 $$aElectronic books.
001445879 77608 $$iPrint version:$$z9811909717$$z9789811909719$$w(OCoLC)1295351440
001445879 830_0 $$aBehaviormetrics - quantitative approaches to human behavior ;$$vvolume 14.
001445879 852__ $$bebk
001445879 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-0972-6$$zOnline Access$$91397441.1
001445879 909CO $$ooai:library.usi.edu:1445879$$pGLOBAL_SET
001445879 980__ $$aBIB
001445879 980__ $$aEBOOK
001445879 982__ $$aEbook
001445879 983__ $$aOnline
001445879 994__ $$a92$$bISE