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A Beginner's Guide to Structural Equation Modeling

Second Edition

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The second edition features:a CD with all of the book's Amos, EQS, and LISREL programs and data sets; new chapters on importing data issues related to data editing and on how to report research; an updated introduction to matrix notation and programs that illustrate how to compute these calculations; many more computer program examples and chapter exercises; and increased coverage of factors that affect correlation, the 4-step approach to SEM and hypothesis testing, significance, power, and sample size issues.The new edition's expanded use of applications make this book ideal for advanced students and researchers in psychology, education, business, health care, political science, sociology, and biology. A basic understanding of correlation is assumed and an understanding of the matrices used in SEM models is encouraged.

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A Beginner's Guide to Structural Equation Modeling, Randall E. Schumacker, Richard G. Lomax

Langue
Année de publication
2004
product-detail.submit-box.info.binding
(souple),
État du livre
Abîmé
Prix
0,37 €

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3,4
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Sous-titre
Second Edition
Langue
Anglais
Publié
2004
Format
souple
Pages
498
ISBN10
0805840184
ISBN13
9780805840186
Séries
Évaluation
3,4 sur 5
Description
The second edition features:a CD with all of the book's Amos, EQS, and LISREL programs and data sets; new chapters on importing data issues related to data editing and on how to report research; an updated introduction to matrix notation and programs that illustrate how to compute these calculations; many more computer program examples and chapter exercises; and increased coverage of factors that affect correlation, the 4-step approach to SEM and hypothesis testing, significance, power, and sample size issues.The new edition's expanded use of applications make this book ideal for advanced students and researchers in psychology, education, business, health care, political science, sociology, and biology. A basic understanding of correlation is assumed and an understanding of the matrices used in SEM models is encouraged.