Advances In Latent Class Analysis
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Advances In Latent Class Analysis
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Author : Gregory R. Hancock
language : en
Publisher: IAP
Release Date : 2019-05-01
Advances In Latent Class Analysis written by Gregory R. Hancock and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-01 with Education categories.
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.
Latent Class And Latent Transition Analysis
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Author : Linda M. Collins
language : en
Publisher: John Wiley & Sons
Release Date : 2013-05-20
Latent Class And Latent Transition Analysis written by Linda M. Collins and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-20 with Mathematics categories.
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.
Applied Latent Class Analysis
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Author : Jacques A. Hagenaars
language : en
Publisher: Cambridge University Press
Release Date : 2002-06-24
Applied Latent Class Analysis written by Jacques A. Hagenaars and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-06-24 with Social Science categories.
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.
An Introduction To Latent Class Analysis
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Author : Nobuoki Eshima
language : en
Publisher: Springer Nature
Release Date : 2022-04-09
An Introduction To Latent Class Analysis written by Nobuoki Eshima and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-09 with Business & Economics categories.
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.
Advances In Latent Variable Mixture Models
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Author : Gregory R. Hancock
language : en
Publisher: IAP
Release Date : 2007-11-01
Advances In Latent Variable Mixture Models written by Gregory R. Hancock and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-01 with Mathematics categories.
The current volume, Advances in Latent Variable Mixture Models, contains chapters by all of the speakers who participated in the 2006 CILVR conference, providing not just a snapshot of the event, but more importantly chronicling the state of the art in latent variable mixture model research. The volume starts with an overview chapter by the CILVR conference keynote speaker, Bengt Muthén, offering a “lay of the land” for latent variable mixture models before the volume moves to more specific constellations of topics. Part I, Multilevel and Longitudinal Systems, deals with mixtures for data that are hierarchical in nature either due to the data’s sampling structure or to the repetition of measures (of varied types) over time. Part II, Models for Assessment and Diagnosis, addresses scenarios for making judgments about individuals’ state of knowledge or development, and about the instruments used for making such judgments. Finally, Part III, Challenges in Model Evaluation, focuses on some of the methodological issues associated with the selection of models most accurately representing the processes and populations under investigation. It should be stated that this volume is not intended to be a first exposure to latent variable methods. Readers lacking such foundational knowledge are encouraged to consult primary and/or secondary didactic resources in order to get the most from the chapters in this volume. Once armed with the basic understanding of latent variable methods, we believe readers will find this volume incredibly exciting.
Latent Class And Latent Transition Analysis
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Author : Linda M. Collins
language : en
Publisher: Wiley
Release Date : 2021-11-23
Latent Class And Latent Transition Analysis written by Linda M. Collins and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-23 with Mathematics categories.
Since the first edition of this book was released, there have been several advances in the methodological literature that address practical challenges to applying Latent class analysis (LCA) and Latent transition analysis (LTA) in real-world data. A second edition of this book is necessary and timely so that these topics can be included. This new edition continues to provide a comprehensive introduction to LCA and LTA for categorical data. This book also continues to cover more advanced material, including multiple-group analyses and models involving covariates. The second edition provides new material on latent profile analysis (LPA) and LCA with an observed outcome. Empirical examples continue to be used frequently to illustrate and reinforce the material, and a data analyst’s perspective continues to be taken throughout. This book is aimed at advanced graduate students and can be used as a textbook in a course on categorical data analysis or latent variable models. It is also suitable as an advanced introduction to LCA and LTA for scientists who wish to apply these approaches in empirical data. This book continues to assume that readers have some familiarity with analysis of contingency tables and with logistic regression. Readers will need a background equivalent to about two semesters of graduate level statistics for the social, behavioral, or biomedical sciences.
Handbook Of Methodological Approaches To Community Based Research
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Author : Leonard Jason
language : en
Publisher: Oxford University Press
Release Date : 2016
Handbook Of Methodological Approaches To Community Based Research written by Leonard Jason and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Psychology categories.
"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"--
Advances In Latent Variables
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Author : Maurizio Carpita
language : en
Publisher: Springer
Release Date : 2015-04-01
Advances In Latent Variables written by Maurizio Carpita and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-01 with Mathematics categories.
The book, belonging to the series “Studies in Theoretical and Applied Statistics– Selected Papers from the Statistical Societies”, presents a peer-reviewed selection of contributions on relevant topics organized by the editors on the occasion of the SIS 2013 Statistical Conference "Advances in Latent Variables. Methods, Models and Applications", held at the Department of Economics and Management of the University of Brescia from June 19 to 21, 2013. The focus of the book is on advances in statistical methods for analyses with latent variables. In fact, in recent years, there has been increasing interest in this broad research area from both a theoretical and an applied point of view, as the statistical latent variable approach allows the effective modeling of complex real-life phenomena in a wide range of research fields. A major goal of the volume is to bring together articles written by statisticians from different research fields, which present different approaches and experiences related to the analysis of unobservable variables and the study of the relationships between them.
Modern Statistical Methods For Hci
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Author : Judy Robertson
language : en
Publisher: Springer
Release Date : 2016-03-22
Modern Statistical Methods For Hci written by Judy Robertson and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-22 with Computers categories.
This book critically reflects on current statistical methods used in Human-Computer Interaction (HCI) and introduces a number of novel methods to the reader. Covering many techniques and approaches for exploratory data analysis including effect and power calculations, experimental design, event history analysis, non-parametric testing and Bayesian inference; the research contained in this book discusses how to communicate statistical results fairly, as well as presenting a general set of recommendations for authors and reviewers to improve the quality of statistical analysis in HCI. Each chapter presents [R] code for running analyses on HCI examples and explains how the results can be interpreted. Modern Statistical Methods for HCI is aimed at researchers and graduate students who have some knowledge of “traditional” null hypothesis significance testing, but who wish to improve their practice by using techniques which have recently emerged from statistics and related fields. This book critically evaluates current practices within the field and supports a less rigid, procedural view of statistics in favour of fair statistical communication.
Handbook Of Advanced Multilevel Analysis
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Author : Joop Hox
language : en
Publisher: Psychology Press
Release Date : 2011-01-11
Handbook Of Advanced Multilevel Analysis written by Joop Hox and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-11 with Psychology categories.
This new handbook is the definitive resource on advanced topics related to multilevel analysis. The editors assembled the top minds in the field to address the latest applications of multilevel modeling as well as the specific difficulties and methodological problems that are becoming more common as more complicated models are developed. Each chapter features examples that use actual datasets. These datasets, as well as the code to run the models, are available on the book’s website http://www.hlm-online.com . Each chapter includes an introduction that sets the stage for the material to come and a conclusion. Divided into five sections, the first provides a broad introduction to the field that serves as a framework for understanding the latter chapters. Part 2 focuses on multilevel latent variable modeling including item response theory and mixture modeling. Section 3 addresses models used for longitudinal data including growth curve and structural equation modeling. Special estimation problems are examined in section 4 including the difficulties involved in estimating survival analysis, Bayesian estimation, bootstrapping, multiple imputation, and complicated models, including generalized linear models, optimal design in multilevel models, and more. The book’s concluding section focuses on statistical design issues encountered when doing multilevel modeling including nested designs, analyzing cross-classified models, and dyadic data analysis. Intended for methodologists, statisticians, and researchers in a variety of fields including psychology, education, and the social and health sciences, this handbook also serves as an excellent text for graduate and PhD level courses in multilevel modeling. A basic knowledge of multilevel modeling is assumed.