An Introduction To Latent Variable Models
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An Introduction To Latent Variable Models
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Author : B. Everett
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-07
An Introduction To Latent Variable Models written by B. Everett and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-07 with Science categories.
Latent variable models are used in many areas of the social and behavioural sciences, and the increasing availability of computer packages for fitting such models is likely to increase their popularity. This book attempts to introduce such models to applied statisticians and research workers interested in exploring the structure of covari ance and correlation matrices in terms of a small number of unob servable constructs. The emphasis is on the practical application of the procedures rather than on detailed discussion of their mathe matical and statistical properties. It is assumed that the reader is familiar with the most commonly used statistical concepts and methods, particularly regression, and also has a fair knowledge of matrix algebra. My thanks are due to my colleagues Dr David Hand and Dr Graham Dunn for helpful comments on the book, to Mrs Bertha Lakey for her careful typing of a difficult manuscript and to Peter Cuttance for assistance with the LlSREL package. In addition the text clearly owes a great deal to the work on structural equation models published by Karl Joreskog, Dag Sorbom, Peter Bentler, Michael Browne and others.
Introduction To Latent Variable Models
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Author : B. S. Everitt
language : en
Publisher:
Release Date : 1984
Introduction To Latent Variable Models written by B. S. Everitt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with categories.
An Introduction To Latent Variable Growth Curve Modeling
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Author : Terry E. Duncan
language : en
Publisher: Routledge
Release Date : 2013-05-13
An Introduction To Latent Variable Growth Curve Modeling written by Terry E. Duncan and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-13 with Business & Economics categories.
This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader’s familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book’s CD. Throughout the book, the authors present a variety of LGM techniques that are useful for many different research designs, and numerous figures provide helpful diagrams of the examples. Updated throughout, the second edition features three new chapters—growth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group issues (analyzing growth in multiple populations, accelerated designs, and multi-level longitudinal approaches), and then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. The model specifications previously included in the appendices are now available on the CD so the reader can more easily adapt the models to their own research. This practical guide is ideal for a wide range of social and behavioral researchers interested in the measurement of change over time, including social, developmental, organizational, educational, consumer, personality and clinical psychologists, sociologists, and quantitative methodologists, as well as for a text on latent variable growth curve modeling or as a supplement for a course on multivariate statistics. A prerequisite of graduate level statistics is recommended.
Generalized Latent Variable Modeling
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Author : Anders Skrondal
language : en
Publisher: CRC Press
Release Date : 2004-05-11
Generalized Latent Variable Modeling written by Anders Skrondal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-05-11 with Mathematics categories.
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wi
Latent Variable Models
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Author : John C. Loehlin
language : en
Publisher: Psychology Press
Release Date : 2004-05-20
Latent Variable Models written by John C. Loehlin and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-05-20 with Business & Economics categories.
This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling more easily. A few sections of the book make use of elementary matrix algebra. An appendix on the topic is provided for those who need a review. The author maintains an informal style so as to increase the book's accessibility. Notes at the end of each chapter provide some of the more technical details. The book is not tied to a particular computer program, but special attention is paid to LISREL, EQS, AMOS, and Mx. New in the fourth edition of Latent Variable Models: *a data CD that features the correlation and covariance matrices used in the exercises; *new sections on missing data, non-normality, mediation, factorial invariance, and automating the construction of path diagrams; and *reorganization of chapters 3-7 to enhance the flow of the book and its flexibility for teaching. Intended for advanced students and researchers in the areas of social, educational, clinical, industrial, consumer, personality, and developmental psychology, sociology, political science, and marketing, some prior familiarity with correlation and regression is helpful.
Latent Variable Models
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Author : John C. Loehlin
language : en
Publisher: Routledge
Release Date : 2016-12-07
Latent Variable Models written by John C. Loehlin and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-07 with Psychology categories.
Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing path diagrams to explain the relationships in the models. This approach helps less mathematically-inclined readers to grasp the underlying relations among path analysis, factor analysis, and structural equation modeling, and to set up and carry out such analyses. This revised and expanded fifth edition again contains key chapters on path analysis, structural equation models, and exploratory factor analysis. In addition, it contains new material on composite reliability, models with categorical data, the minimum average partial procedure, bi-factor models, and communicating about latent variable models. The informal writing style and the numerous illustrative examples make the book accessible to readers of varying backgrounds. Notes at the end of each chapter expand the discussion and provide additional technical detail and references. Moreover, most chapters contain an extended example in which the authors work through one of the chapter’s examples in detail to aid readers in conducting similar analyses with their own data. The book and accompanying website provide all of the data for the book’s examples as well as syntax from latent variable programs so readers can replicate the analyses. The book can be used with any of a variety of computer programs, but special attention is paid to LISREL and R. An important resource for advanced students and researchers in numerous disciplines in the behavioral sciences, education, business, and health sciences, Latent Variable Models is a practical and readable reference for those seeking to understand or conduct an analysis using latent variables.
An Introduction To Latent Variable Growth Curve Modeling
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Author : Terry E. Duncan
language : en
Publisher: Routledge
Release Date : 2006
An Introduction To Latent Variable Growth Curve Modeling written by Terry E. Duncan and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Mathematics categories.
This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader's familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book's CD. Throughout the book, the authors present a variety of LGM techniques that are useful for many different research designs, and numerous figures provide helpful diagrams of the examples. Updated throughout, the second edition features three new chapters--growth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group issues (analyzing growth in multiple populations, accelerated designs, and multi-level longitudinal approaches), and then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. The model specifications previously included in the appendices are now available on the CD so the reader can more easily adapt the models to their own research. This practical guide is ideal for a wide range of social and behavioral researchers interested in the measurement of change over time, including social, developmental, organizational, educational, consumer, personality and clinical psychologists, sociologists, and quantitative methodologists, as well as for a text on latent variable growth curve modeling or as a supplement for a course on multivariate statistics. A prerequisite of graduate level statistics is recommended.
Latent Variable Models
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Author : John C. Loehlin
language : en
Publisher: Psychology Press
Release Date : 1992
Latent Variable Models written by John C. Loehlin and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Factor analysis categories.
This book provides an introduction to a rapidly-growing area in the social and behavioral sciences -- the modeling of systems in which one or more variables are hypothesized, but not directly observed. Providing a conceptually unified treatment of modeling of this type -- exploratory and confirmatory factor analysis, path analysis, and structural equation analysis -- it is intended to introduce these techniques to individuals who have had some exposure to statistical methods in general, but are beginners in this particular area. Using an inductive and informal approach, it emphasizes the use of path diagrams and a variety of concrete examples, and keeps the mathematics largely intuitive. Examples are drawn from a variety of fields, including psychometrics, sociology, psychology, education and behavior genetics. Although some introductory material is provided for LISREL, EQS, and CALIS, and for exploratory factor analysis programs in SAS, SPSS, and BMPD, the book is not closely tied to any one computer program or statistical package.
Latent Variable Modeling Using R
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Author : A. Alexander Beaujean
language : en
Publisher: Routledge
Release Date : 2014-05-09
Latent Variable Modeling Using R written by A. Alexander Beaujean and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-09 with Psychology categories.
This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs. Featuring examples applicable to psychology, education, business, and other social and health sciences, minimal text is devoted to theoretical underpinnings. The material is presented without the use of matrix algebra. As a whole the book prepares readers to write about and interpret LVM results they obtain in R. Each chapter features background information, boldfaced key terms defined in the glossary, detailed interpretations of R output, descriptions of how to write the analysis of results for publication, a summary, R based practice exercises (with solutions included in the back of the book), and references and related readings. Margin notes help readers better understand LVMs and write their own R syntax. Examples using data from published work across a variety of disciplines demonstrate how to use R syntax for analyzing and interpreting results. R functions, syntax, and the corresponding results appear in gray boxes to help readers quickly locate this material. A unique index helps readers quickly locate R functions, packages, and datasets. The book and accompanying website at http://blogs.baylor.edu/rlatentvariable/ provides all of the data for the book’s examples and exercises as well as R syntax so readers can replicate the analyses. The book reviews how to enter the data into R, specify the LVMs, and obtain and interpret the estimated parameter values. The book opens with the fundamentals of using R including how to download the program, use functions, and enter and manipulate data. Chapters 2 and 3 introduce and then extend path models to include latent variables. Chapter 4 shows readers how to analyze a latent variable model with data from more than one group, while Chapter 5 shows how to analyze a latent variable model with data from more than one time period. Chapter 6 demonstrates the analysis of dichotomous variables, while Chapter 7 demonstrates how to analyze LVMs with missing data. Chapter 8 focuses on sample size determination using Monte Carlo methods, which can be used with a wide range of statistical models and account for missing data. The final chapter examines hierarchical LVMs, demonstrating both higher-order and bi-factor approaches. The book concludes with three Appendices: a review of common measures of model fit including their formulae and interpretation; syntax for other R latent variable models packages; and solutions for each chapter’s exercises. Intended as a supplementary text for graduate and/or advanced undergraduate courses on latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, business, economics, and social and health sciences, this book also appeals to researchers in these fields. Prerequisites include familiarity with basic statistical concepts, but knowledge of R is not assumed.
An Introduction To Latent Variable Growth Curve Modeling
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Author : Terry E. Duncan
language : en
Publisher: Psychology Press
Release Date : 1999
An Introduction To Latent Variable Growth Curve Modeling written by Terry E. Duncan and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Mathematics categories.
This volume presents a statistical method, known as Latent Variable Growth Curve Modeling, for analyzing repeated measures. Although a number of readers may be unfamiliar with Latent Growth Modeling (LGM), it is likely that most have already mastered many of the method's underpinnings, inasmuch as repeated measures analysis of variance (ANOVA) models are special cases of LGMs that focus only on the factor means. In contrast, a fully expanded latent growth curve analysis takes into account both factor means and variances. This combination of individual and group levels of analysis is unique to the LGM procedure. LGMs are also variants of the standard linear structural model. In addition to using regression coefficents and variances and covariances of the independent variables, they incorporate a mean structure into the model. LGMs strongly resemble the classic confirmatory factor analysis. However, because they use repeated measures raw-score data, the latent factors are interpreted as chronometric common factors representing individual differences over time.