Higher-Order Growth Curves and Mixture Modeling with Mplus (Multivariate Applications Series)

Product Description This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps.The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two using normal and non-normal (e.g., categorical) data. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book’s datasets are available on the web.New to this edition:* Two new chapters providing a stepwise introduction and practical guide to the application of second-order growth curves and mixture models with categorical outcomes using the Mplus program. Complete with exercises, answer keys, and downloadable data files.* Updated illustrative examples using Mplus 8.0 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data.This text is ideal for use in graduate courses or workshops on advanced structural equation, multilevel, longitudinal or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) across the social and behavioral sciences. Review "This book goes way beyond the basics of growth curve modeling. The authors manage to explain complicated and potentially confusing models like factor-of-curves and curve-of-factors very well. I like the way they explain how to interpret the models, including substantive interpretations of real world examples."Joop Hox, Utrecht University, The Netherlands"This timely work gives clear statistical advice and offers step-by-step coverage for Mplus users in the analysis of many kinds of growth curve models and also mixture models. A wealth of syntax examples and available data sets give additional opportunities for practice." Rex Kline, Concordia University, Canada"This book would be an excellent addition to graduate courses on the analysis of longitudinal data, advanced courses on structural equation modeling and multilevel regression, or for a workshop on how to conduct growth curve modeling analysis. This would also be an excellent resource for researchers conducting analyses of longitudinal data." Daniel W. Russell, Iowa State University, USA"The authors’ approach to explaining statistical analysis is one of the best I've seen, and each chapter is clear and easy to read. ... I would recommend it to people attending courses I run in the Quantitative Research Methods Training Unit. ... This project fills a significant gap ... by providing step by step procedures in the application of latent growth modelling techniques and translating complicated statistical language into simple English." D. Daniel Boduszek, University of Huddersfield, UK"This book has the potential to contribute greatly to the field. ... A resource that integrates ... Mplus with the analysis of different kinds of growth models will be widely used. ... The style is straightforward and easy to follow. ... I would consider adopting it for my graduate course ... Longitudinal Research Methods & Analysis. ... I would seriously consider ... using it for both research and teaching needs." Joel Hektner, North Dakota State University, USA"Examples are provided to help researchers see how to apply the methodology with actual data, and interpret the results. ... The book will be of interest to students, faculty and researchers working with longitudinal data in su

Wickrama, Kandauda

Lee, Tae Kyoung

O’Neal, Catherine Walker

Lorenz, Frederick

Reference

Routledge

This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. 
The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two using normal and non-normal (e.g., categorical) data. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book’s datasets are available on the web. 
New to this edition: 
* Two new chapters providing a stepwise introduction and practical guide to the application of second-order growth curves and mixture models with categorical outcomes using the Mplus program. Complete with exercises, answer keys, and downloadable data files. 
* Updated illustrative examples using Mplus 8.0 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data. 
This text is ideal for use in graduate courses or workshops on advanced structural equation, multilevel, longitudinal or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) across the social and behavioral sciences.

The Life Of Alcuin (1837)

Biographies & Memoirs

Arts & Literature

Kessinger Publishing

This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book’s datasets are available on the web. Highlights include: -Illustrative examples using Mplus 7.4 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data. -Exercises with an answer key allow readers to practice the skills they learn. -Applications to a variety of disciplines appeal to those in the behavioral, social, political, educational, occupational, business, and health sciences.  -Data files for all the illustrative examples and exercises at www.routledge.com/9781138925151 allow readers to test their understanding of the concepts. -Point to Remember boxes aid in reader comprehension or provide in-depth discussions of key statistical or theoretical concepts. Part 1 introduces basic structural equation modeling (SEM) as well as first- and second-order growth curve modeling. The book opens with the basic concepts from SEM, possible extensions of conventional growth curve models, and the data and measures used throughout the book. The subsequent chapters in part 1 explain the extensions. Chapter 2 introduces conventional modeling of multidimensional panel data, including confirmatory factor analysis (CFA) and growth curve modeling, and its limitations. The logical and theoretical extension of a CFA to a second-order growth curve, known as curve-of-factors model (CFM), are explained in Chapter 3. Chapter 4 illustrates the estimation and interpretation of unconditional and conditional CFMs. Chapter 5 presents the logical and theoretical extension of a parallel process model to a second-order growth curve, known as factor-of-curves model (FCM). Chapter 6 illustrates the estimation and interpretation of unconditional and conditional FCMs. Part 2 reviews growth mixture modeling including unconditional growth mixture modeling (Ch. 7) and conditional growth mixture models (Ch. 8). How to extend second-order growth curves (curve-of-factors and factor-of-curves models) to growth mixture models is highlighted in Chapter 9.  Ideal as a supplement for use in graduate courses on (advanced) structural equation, multilevel, longitudinal, or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) taught in psychology, human development and family studies, business, education, health, and social sciences, this book’s practical approach also appeals to researchers. Prerequisites include a basic knowledge of intermediate statistics and structural equation modeling.  

Higher-Order Growth Curves and Mixture Modeling with Mplus: A Practical Guide (Multivariate Applications Series)

This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book’s datasets are available on the web.
Highlights include: -Illustrative examples using Mplus 7.4 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data. -Exercises with an answer key allow readers to practice the skills they learn. -Applications to a variety of disciplines appeal to those in the behavioral, social, political, educational, occupational, business, and health sciences. -Data files for all the illustrative examples and exercises at www.routledge.com/9781138925151 allow readers to test their understanding of the concepts.
-Point to Remember boxes aid in reader comprehension or provide in-depth discussions of key statistical or theoretical concepts. Part 1 introduces basic structural equation modeling (SEM) as well as first- and second-order growth curve modeling. The book opens with the basic concepts from SEM, possible extensions of conventional growth curve models, and the data and measures used throughout the book. The subsequent chapters in part 1 explain the extensions. Chapter 2 introduces conventional modeling of multidimensional panel data, including confirmatory factor analysis (CFA) and growth curve modeling, and its limitations. The logical and theoretical extension of a CFA to a second-order growth curve, known as curve-of-factors model (CFM), are explained in Chapter 3. Chapter 4 illustrates the estimation and interpretation of unconditional and conditional CFMs. Chapter 5 presents the logical and theoretical extension of a parallel process model to a second-order growth curve, known as factor-of-curves model (FCM). Chapter 6 illustrates the estimation and interpretation of unconditional and conditional FCMs. Part 2 reviews growth mixture modeling including unconditional growth mixture modeling (Ch. 7) and conditional growth mixture models (Ch. 8). How to extend second-order growth curves (curve-of-factors and factor-of-curves models) to growth mixture models is highlighted in Chapter 9. Ideal as a supplement for use in graduate courses on (advanced) structural equation, multilevel, longitudinal, or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) taught in psychology, human development and family studies, business, education, health, and social sciences, this book’s practical approach also appeals to researchers. Prerequisites include a basic knowledge of intermediate statistics and structural equation modeling.

The Life of Alcuin

Nabu Press

TALL, DARK AND DEAD Tina Van Lube is being blackmailed by a disreputable ex-lover, so she hires detective Lou Lait to get her incriminating love letters back. All in a day's work for Lait. Except for one small detail--the disreputable ex-lover, columnist Erskine Spalding, is found dead with a knife in his back. Suspects abound: Tina's husband Jan, disfigured war hero; Tina's hot-headed brother, Stanislaus; Coates, the recently-fired butler; plain-but-dedicated secretary, Prescott; the gun-running Colonel; the social-climbing Durkins...even Lolita, the dancer. They all had their reasons for quieting the nasty gossip columnist. Lait's making it his job to find out who did the deed. THE SAVAGE CHASE Everybody wants Stallings. Stallings is rich and when he gets drunk all he wants to do is gamble...and he always loses. So when a clever cabbie ends up with Stallings passed out in the back of his taxi, he takes him to a hotel room and trades the man to gambler Lee Mayo for some quick cash. Mayo has been carrying on with Stallings wife, but agrees to the exchange, and then tells her where he is. So they hustle over to the hotel, only to find that someone has already picked him up. Now the word is beginning to spread and fellow gambler Ernie Wiles becomes involved, a man much more ruthless than Mayo and determined to find Stallings first. They all want Stallings--what they don't know is that Stallings is completely broke! RUN THE WILD RIVER The two deputies escort Bill Ackroyd out of Juarez, kick him around a little, and take all his money. Bleeding and thirsty, he meets Manuel, who gets him back on his feet. Manuel has been leading his fellow Mexicans across the Rio Grande as cheap Texas labor, but having seen the error of his ways, wants Ackroyd to help him break up the illegal business. Ackroyd sees a perfect opportunity, and joins the human traffickers instead. Soon he meets Maria, and figures out how they can make some real money by finding out who controls the whole setup. It's all going so well. Until blonde, beautiful Gail Graham comes to town...

Tall, Dark and Dead / The Savage Chase / Run the Wild River

Mystery, Thriller & Suspense

Champion, D. L.

Jaediker, Kermit

Mystery

Stark House Press

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