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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: New.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 75,92
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Aggiungi al carrelloCondizione: new.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2014
ISBN 10: 1848726996 ISBN 13: 9781848726994
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. 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 provides all of the data for the books 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 chapters 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
EUR 75,02
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Aggiungi al carrelloCondizione: New. In.
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Prima edizione
EUR 76,77
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Aggiungi al carrelloCondizione: New. . 2014. 1st Edition. Paperback. . . . .
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 72,97
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
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Aggiungi al carrelloPF. Condizione: New.
Condizione: New. pp. 218.
EUR 90,57
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Aggiungi al carrelloCondizione: New. pp. 218.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 84,25
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Condizione: New. . 2014. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.
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Aggiungi al carrelloPaperback. Condizione: Brand New. 1st edition. 218 pages. 10.75x8.25x0.50 inches. In Stock.
EUR 77,45
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. A. Alexander Beaujean is an Associate Professor in Educational Psychology at Baylor University.This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusi.
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Aggiungi al carrelloPaperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
EUR 64,25
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Latent Variable Modeling Using R | A Step-by-Step Guide | A. Alexander Beaujean | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2014 | Routledge | EAN 9781848726994 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2014
ISBN 10: 1848726996 ISBN 13: 9781848726994
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 127,03
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. 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 provides all of the data for the books 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 chapters 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 66,38
Quantità: 5 disponibili
Aggiungi al carrelloPaperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Da: Majestic Books, Hounslow, Regno Unito
EUR 77,25
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. 218 Author CRC with Latin Modern Roman font This item is printed on demand.