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Data Analysis with Mplus (Methodology in the Social Sciences) - Softcover

Buch 8 von 33: Methodology in the Social Sciences

Geiser, Christian (Utah State University, USA)

 
9781462502455: Data Analysis with Mplus (Methodology in the Social Sciences)

Inhaltsangabe

A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with real data examples, numerous screen shots, and output excerpts. The author shows how to prepare a data set for import in Mplus using SPSS. He explains how to specify different types of models in Mplus syntax and address typical caveats--for example, assessing measurement invariance in longitudinal SEMs. Coverage includes path and factor analytic models as well as mediational, longitudinal, multilevel, and latent class models. Specific programming tips and solution strategies are presented in boxes in each chapter. The companion website (www.guilford.com/geiser-materials) features data sets, annotated syntax files, and output for all of the examples. Of special utility to instructors and students, many of the examples can be run with the free demo version of Mplus.

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Über die Autorinnen und Autoren

Christian Geiser, PhD, is CEO of Quantfish and former Professor of Psychology at Utah State University. His research interests are in psychometrics and structural equation modeling, particularly in longitudinal data analysis and multitrait–multimethod modeling. As part of his methodological work, he has presented new longitudinal structural equation modeling approaches for examining effects of situations and person–situation interactions, as well as models for integrating information from multiple reporters or other methods in longitudinal analyses. He offers Mplus workshops at www.goquantfish.com.


Christian Geiser, PhD, is Professor of Psychology at Utah State University and Director of the Quantitative Psychology PhD Specialization. His research interests are in psychometrics and structural equation modeling, particularly in longitudinal data analysis and multitrait–multimethod modeling. As part of his methodological work, he has presented new longitudinal structural equation modeling approaches for examining effects of situations and person–situation interactions, as well as models for integrating information from multiple reporters or other methods in longitudinal analyses.

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