Описание: Helping students to successfully visualise SEM by drawing on the graphical interface of EQS and providing plenty of screenshots throughout, this book assumes no prior statistical knowledge and includes practical assistance to encourage students to feel confident about using SEM for their research project.
Автор: Silva, Bruno Castanho Название: Multilevel structural equation modeling ISBN: 1544323050 ISBN-13(EAN): 9781544323053 Издательство: Sage Publications Рейтинг: Цена: 5859.00 р. Наличие на складе: Поставка под заказ.
Описание: Multilevel Structural Equation Modeling by Bruno Castanho Silva, Constantin Manuel Bosancianu, and Levente Littvay serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the social sciences. As the first book of its kind, this title is an accessible, hands-on introduction for beginners of the topic. The authors predict a growth in this area, fueled by both data availability and also the availability of new and improved software to run these models. The applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra guarantee that this volume will be useful to social science graduate students wanting to utilize such models.
Автор: Blunch Niels Название: Introduction to Structural Equation Modeling Using IBM SPSS ISBN: 144624900X ISBN-13(EAN): 9781446249000 Издательство: Sage Publications Рейтинг: Цена: 9346.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This comprehensive second edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM).
Автор: Byrne Название: Structural Equation Modeling with Mplus ISBN: 0805859861 ISBN-13(EAN): 9780805859867 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Modeled after Barbara Byrne's other best-selling structural equation modeling (SEM) books, this practical guide reviews the basic concepts and applications of SEM using Mplus Versions 5 & 6. The author reviews SEM applications based on actual data taken from her own research. Using non-mathematical language, it is written for the novice SEM user. With each application chapter, the author "walks" the reader through all steps involved in testing the SEM model including:
an explanation of the issues addressed
illustrated and annotated testing of the hypothesized and post hoc models
explanation and interpretation of all Mplus input and output files
important caveats pertinent to the SEM application under study
a description of the data and reference upon which the model was based
the corresponding data and syntax files available at http: //www.psypress.com/sem-with-mplus/datasets .
The first two chapters introduce the fundamental concepts of SEM and important basics of the Mplus program. The remaining chapters focus on SEM applications and include a variety of SEM models presented within the context of three sections: Single-group analyses, Multiple-group analyses, and other important topics, the latter of which includes the multitrait-multimethod, latent growth curve, and multilevel models.
Intended for researchers, practitioners, and students who use SEM and Mplus, this book is an ideal resource for graduate level courses on SEM taught in psychology, education, business, and other social and health sciences and/or as a supplement for courses on applied statistics, multivariate statistics, intermediate or advanced statistics, and/or research design. Appropriate for those with limited exposure to SEM or Mplus, a prerequisite of basic statistics through regression analysis is recommended.
Описание: Using a tried-and-tested, five-step process, this book provides students with a reader-friendly introduction to the major types of structural equation models implemented in the Mplus framework.
Описание: Helping students to successfully visualise SEM by drawing on the graphical interface of EQS and providing plenty of screenshots throughout, this book assumes no prior statistical knowledge and includes practical assistance to encourage students to feel confident about using SEM for their research project.
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