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Latent Growth Curve Modeling (Quantitative Applications in the Social Sciences) (Englisch) Taschenbuch – 27. Juni 2008


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Produktinformation

Produktbeschreibungen

Synopsis

Latent growth curve modelling (LGM) is an indispensable and increasingly ubiquitous approach for modelling longitudinal data. This book introduces LGM techniques to researchers, provides easy-to-follow, didactic examples of several common growth modelling approaches and highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit.

Über den Autor und weitere Mitwirkende

Kristopher J. Preacher, Ph.D. is an assistant professor of Quantitative Psychology at the University of Kansas. His research focuses primarily on the use of factor analysis, structural equation modeling, and multilevel modeling to analyze longitudinal and correlational data. Other interests include developing techniques to test mediation and moderation hypotheses, bridging the gap between theory and practice, and studying model evaluation and model selection in the application of multivariate methods to social science questions.

Aaron L. Wichman is a doctoral candidate in the Social Psychology program at The Ohio State University, where he serves as coordinator for the department's introductory social psychology courses. His research interests focus on social cognition and the application of quantitative techniques to individual differences research, including personality assessment.

Robert C. MacCallum, Ph.D. has had a long and distinguished career as a respected quantitative psychologist. His primary research interests involve the study of quantitative models and methods for the study of correlational data, especially factor analysis, structural equation modeling, and multilevel modeling. Of particular interest is the use of such methods for the analysis of longitudinal data, with a focus on individual differences in patterns of change over time. He teaches courses in factor analysis and introductory and advanced structural equation modeling. He currently serves as the program chair of the L. L. Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill.

Nancy E. Briggs, Ph.D. is a statistician in the Discipline of Public Health at the University of Adelaide. She serves primarily as a data analyst in various research projects in the health and behavioral sciences. Her research and professional interests involve the application of advanced multivariate statistical techniques, such as linear and nonlinear multilevel models and latent variable models, to empirical data.

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Amazon.com: 3.6 von 5 Sternen 7 Rezensionen
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen awesome 24. Dezember 2012
Von jf - Veröffentlicht auf Amazon.com
Format: Kindle Edition Verifizierter Kauf
Great and easy to understand. Not too technical but detailed enough for a great general understanding of the technique. Would buy again. Hard to find books on LGCM and this is perfect
3.0 von 5 Sternen If you are a statistician (I am not) and you enjoy drilling down into the equations to see how growth ... 27. Mai 2015
Von Michael R - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
Overall, this is a VERY math intensive resource. I have a fairly strong background in math - I had completed four calculus courses as well as linear and matrix algebra in college. But I am a bit rusty, which made getting through this book a challenge. If you are a statistician (I am not) and you enjoy drilling down into the equations to see how growth models are derived, this is probably a great resource for you. If you are looking for a straight-forward guide that gives enough of the math to make sense of the modeling but that focuses more upon the purpose of growth models and applications, I would recommend Todd Little's text.
5.0 von 5 Sternen Five Stars 24. April 2015
Von Ariya - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
Great book about LGC model! A Brief and detailed examples.
0 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen A great little resource 12. August 2013
Von Andrew F. Hayes - Veröffentlicht auf Amazon.com
Format: Taschenbuch
I have referred many people interested in getting started with latent growth modeling to this little powerhouse of a book written by some powerhouse scholars. What a bargain for under $20. It is worth much more than that.
1 von 3 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Statistics Rule!!!! 8. Januar 2013
Von Jonathan Gallimore - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
I think that Latent Growth Curve Modeling will be a great tool in the future but right now it is ahead of its time. I cannot imagine taking Structural Equation Modeling without this book.
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