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Author: C. Mitchell Dayton
Publisher: SAGE
ISBN: 9780761913238
Category : Medical
Languages : en
Pages : 108
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Book Description
The author presents an accessible guide to latent class scaling models for binary response variables. Covered in the book are: a survey on academic cheating; children's mastery of spatial tasks; medical diagnosis of lung disease.
Author: C. Mitchell Dayton
Publisher: SAGE
ISBN: 9780761913238
Category : Medical
Languages : en
Pages : 108
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Book Description
The author presents an accessible guide to latent class scaling models for binary response variables. Covered in the book are: a survey on academic cheating; children's mastery of spatial tasks; medical diagnosis of lung disease.
Author: Jacques A. Hagenaars
Publisher: Cambridge University Press
ISBN: 1139439235
Category : Social Science
Languages : en
Pages : 478
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Book Description
Applied Latent Class Analysis introduces several innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis contributed essays to this volume, each presenting a key innovation to the basic latent class model and illustrating how it can prove useful in situations typically encountered in actual research.
Author: Gregory R. Hancock
Publisher: IAP
ISBN: 1641135638
Category : Education
Languages : en
Pages : 281
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Book Description
What is latent class analysis? If you asked that question thirty or forty years ago you would have gotten a different answer than you would today. Closer to its time of inception, latent class analysis was viewed primarily as a categorical data analysis technique, often framed as a factor analysis model where both the measured variable indicators and underlying latent variables are categorical. Today, however, it rests within much broader mixture and diagnostic modeling framework, integrating measured and latent variables that may be categorical and/or continuous, and where latent classes serve to define the subpopulations for whom many aspects of the focal measured and latent variable model may differ. For latent class analysis to take these developmental leaps required contributions that were methodological, certainly, as well as didactic. Among the leaders on both fronts was C. Mitchell “Chan” Dayton, at the University of Maryland, whose work in latent class analysis spanning several decades helped the method to expand and reach its current potential. The current volume in the Center for Integrated Latent Variable Research (CILVR) series reflects the diversity that is latent class analysis today, celebrating work related to, made possible by, and inspired by Chan’s noted contributions, and signaling the even more exciting future yet to come.
Author: C. Mitchel Dayton
Publisher:
ISBN: 9781412984720
Category :
Languages : en
Pages :
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Book Description
Author: Allan L. McCutcheon
Publisher: SAGE
ISBN: 9780803927520
Category : Mathematics
Languages : en
Pages : 104
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Book Description
Latent class analysis is a powerful tool for analyzing the structure of relationships among categorically scored variables. It enables researchers to explore the suitability of combining two or more categorical variables into typologies or scales. It also provides a method for testing hypotheses regarding the latent structure among categorical variables.
Author: Leonard Jason
Publisher: Oxford University Press
ISBN: 0190243651
Category : Education
Languages : en
Pages : 409
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Book Description
The Handbook of Methodological Approaches to Community-Based Research is intended to aid the community-oriented researcher in learning about and applying cutting-edge quantitative, qualitative, and mixed methods approaches.
Author: Nobuoki Eshima
Publisher: Springer Nature
ISBN: 9811909725
Category : Business & Economics
Languages : en
Pages : 196
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Book Description
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.
Author: David A. Hensher
Publisher: Cambridge University Press
ISBN: 1107092647
Category : Business & Economics
Languages : en
Pages : 1219
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Book Description
A fully updated second edition of this popular introduction to applied choice analysis, written for graduate students, researchers, professionals and consultants.
Author: R. Langeheine
Publisher: Springer Science & Business Media
ISBN: 1475756445
Category : Psychology
Languages : en
Pages : 309
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Book Description
This volume is based on an international conference held at the Institute for Science Education (IPN) in Kiel in August 1985. The IPN is a national research institute for science education of the Federal Republic of Germany associated with the University of Kiel. The aim of this conference-to treat latent trait and latent class models under comparative points of view as well as under application aspects-was realized in many stimulating contributions and very different ways. We asked the authors of these papers to work out their contributions for publication here, not only because many of the papers present new material, but also because the time is ripe for a comprehen sive volume, working up the widespread literature of the past ten years in this field. We have tried to compile a volume that will be of interest to statistically oriented researchers in a variety of disciplines, including psychology, sociology, education, political science, epidemiology, and the like. Although the chapters assume a reasonably high level of methodo logical sophistication, we hope that the book will find its way into advanced courses in the above fields. We are grateful to the IPN for organizing the conference, to our contributors for their untiring efforts in revising their chapters for publication, and to the staff of Plenum Publishing Corporation for helping to make this book a reality.
Author: Linda M. Collins
Publisher: John Wiley & Sons
ISBN: 111821076X
Category : Mathematics
Languages : en
Pages : 273
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Book Description
A modern, comprehensive treatment of latent class and latent transition analysis for categorical data On a daily basis, researchers in the social, behavioral, and health sciences collect information and fit statistical models to the gathered empirical data with the goal of making significant advances in these fields. In many cases, it can be useful to identify latent, or unobserved, subgroups in a population, where individuals' subgroup membership is inferred from their responses on a set of observed variables. Latent Class and Latent Transition Analysis provides a comprehensive and unified introduction to this topic through one-of-a-kind, step-by-step presentations and coverage of theoretical, technical, and practical issues in categorical latent variable modeling for both cross-sectional and longitudinal data. The book begins with an introduction to latent class and latent transition analysis for categorical data. Subsequent chapters delve into more in-depth material, featuring: A complete treatment of longitudinal latent class models Focused coverage of the conceptual underpinnings of interpretation and evaluationof a latent class solution Use of parameter restrictions and detection of identification problems Advanced topics such as multi-group analysis and the modeling and interpretation of interactions between covariates The authors present the topic in a style that is accessible yet rigorous. Each method is presented with both a theoretical background and the practical information that is useful for any data analyst. Empirical examples showcase the real-world applications of the discussed concepts and models, and each chapter concludes with a "Points to Remember" section that contains a brief summary of key ideas. All of the analyses in the book are performed using Proc LCA and Proc LTA, the authors' own software packages that can be run within the SAS® environment. A related Web site houses information on these freely available programs and the book's data sets, encouraging readers to reproduce the analyses and also try their own variations. Latent Class and Latent Transition Analysis is an excellent book for courses on categorical data analysis and latent variable models at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners in the social, behavioral, and health sciences who conduct latent class and latent transition analysis in their everyday work.
