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Data Analysis with Mplus

Release on 2012-11-142012-11-14 by Christian Geiser
Data Analysis with Mplus

Author: Christian Geiser

Publisher: Guilford Press

ISBN: 9781462502455

Category: Social Science

Page: 305

View: 673

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 (http://crmda.ku.edu/guilford/geiser) 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.
Social Science
Data Analysis with Mplus
Language: en
Pages: 305

Data Analysis with Mplus

Authors: Christian Geiser
Categories: Social Science
Type: BOOK - Published: 2012-11-14 - Publisher: Guilford Press

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
Advanced Multivariate Data Analysis with Mplus
Language: en
Pages: 300

Advanced Multivariate Data Analysis with Mplus

Authors: Christian Geiser, Claudia Crayen, Craig Enders
Categories: Education
Type: BOOK - Published: 2016-05-02 - Publisher: Springer VS

Der zweite Band von "Datenanalyse mit Mplus" wendet sich an fortgeschrittene Anwender, die über solides statistisches Hintergrundwissen und erste Mplus-Kenntnisse verfügen. Wie geht man mit ordinalen oder dichtomen Variablen um? Wie mit einer Verletzung der Nomalverteilungsannahme? In vielen Forschungskontexten steht die Betrachtung mehrerer Gruppen im Vordergrund, andernorts sucht man nach
Studyguide for Data Analysis with Mplus by Geiser, Christian, ISBN 9781462502455
Language: en
Pages: 66

Studyguide for Data Analysis with Mplus by Geiser, Christian, ISBN 9781462502455

Authors: Cram101 Textbook Reviews
Categories: Education
Type: BOOK - Published: 2014-06-13 - Publisher: Cram101

Never HIGHLIGHT a Book Again! Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9781462502455. This item is printed on demand.
The Fluency Construct
Language: en
Pages: 386

The Fluency Construct

Authors: Kelli D. Cummings, Yaacov Petscher
Categories: Psychology
Type: BOOK - Published: 2015-12-11 - Publisher: Springer

This book provides a comprehensive overview of fluency as a construct and its assessment in the context of curriculum-based measurement (CBM). Comparing perspectives from language acquisition, reading, and mathematics, the book parses the vagueness and complexities surrounding fluency concepts and their resulting impact on testing, intervention, and students' educational development.
Principles and Practice of Structural Equation Modeling, Fourth Edition
Language: en
Pages: 534

Principles and Practice of Structural Equation Modeling, Fourth Edition

Authors: Rex B. Kline
Categories: Social Science
Type: BOOK - Published: 2015-11-03 - Publisher: Guilford Publications

New to This Edition *Extensively revised to cover important new topics: Pearl' s graphing theory and SCM, causal inference frameworks, conditional process modeling, path models for longitudinal data, item response theory, and more. *Chapters on best practices in all stages of SEM, measurement invariance in confirmatory factor analysis, and significance

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