LEADER 01165oas 22004573 450 001 9910626159903321 005 20250604213024.0 011 $a2326-3288 035 $a(OCoLC)825110096 035 $a(CONSER) 2013204001 035 $a(CKB)2560000000097293 035 $a(EXLCZ)992560000000097293 100 $a20130125a20uu9999 sy a 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$a... IEEE IAS Electrical Safety Workshop 210 1$aPiscataway, NJ :$cIEEE 300 $aProceedings of conference. 311 08$a2326-330X 517 3 $aESW ... 531 0 $aIEEE IAS Electr. Saf. Workshop 608 $aPeriodicals.$2fast 676 $a621.3 712 02$aInstitute of Electrical and Electronics Engineers. 801 0$bDLC 801 1$bDLC 801 2$bOCLCQ 801 2$bOCLCA 801 2$bVT2 801 2$bOCLCF 801 2$bUUM 801 2$bOCLCQ 801 2$bYWS 801 2$bOCLCL 906 $aCONFERENCE 912 $a9910626159903321 996 $a.. IEEE IAS Electrical Safety Workshop$91886809 997 $aUNINA LEADER 03664nam 22005655 450 001 9910559397503321 005 20251113195132.0 010 $a9789811909726$b(electronic bk.) 010 $z9789811909719 024 7 $a10.1007/978-981-19-0972-6 035 $a(MiAaPQ)EBC6950795 035 $a(Au-PeEL)EBL6950795 035 $a(CKB)21500575800041 035 $a(PPN)262171074 035 $a(OCoLC)1310619864 035 $a(DE-He213)978-981-19-0972-6 035 $a(EXLCZ)9921500575800041 100 $a20220409d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 13$aAn Introduction to Latent Class Analysis $eMethods and Applications /$fby Nobuoki Eshima 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (196 pages) 225 1 $aBehaviormetrics: Quantitative Approaches to Human Behavior,$x2524-4035 ;$v14 311 08$aPrint version: Eshima, Nobuoki An Introduction to Latent Class Analysis Singapore : Springer Singapore Pte. Limited,c2022 9789811909719 327 $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. 330 $aThis book provides methods and applications of latent class analysis, and the following topics are taken up in the focus of discussion: basic latent structure models in a framework of generalized linear models, exploratory latent class analysis, latent class analysis with ordered latent classes, a latent class model approach for analyzing learning structures, the latent Markov analysis for longitudinal data, and path analysis with latent class models. The maximum likelihood estimation procedures for latent class models are constructed via the expectation?maximization (EM) algorithm, and along with it, latent profile and latent trait models are also treated. Entropy-based discussions for latent class models are given as advanced approaches, for example, comparison of latent classes in a latent class cluster model, assessing latent class models, path analysis, and so on. In observing human behaviors and responses to various stimuli and test items, it is valid to assume they are dominatedby certain factors. This book plays a significant role in introducing latent structure analysis to not only young researchers and students studying behavioral sciences, but also to those investigating other fields of scientific research. . 410 0$aBehaviormetrics: Quantitative Approaches to Human Behavior,$x2524-4035 ;$v14 606 $aStatistics 606 $aPsychometrics 606 $aStatistics in Business, Management, Economics, Finance, Insurance 606 $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences 606 $aPsychometrics 615 0$aStatistics. 615 0$aPsychometrics. 615 14$aStatistics in Business, Management, Economics, Finance, Insurance. 615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aPsychometrics. 676 $a150.1943 700 $aEshima$b Nobuoki$01017964 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910559397503321 996 $aAn Introduction to Latent Class Analysis$92832701 997 $aUNINA