A Beginner's Guide to Structural Equation Modeling
By: Lomax, Richard G
| Schumacker, Randall E.
Material type: 
BookPublisher: Mahwah, New Jersey and London, Lawrence Erlbaum Associates 2004Edition: 2nd ed.Description: 498 pages.ISBN: 0-8058-4018-4.Subject(s): statistical method | regression analysis | correlaton | Structural Equation ModelingOnline resources: Publisher's website Summary: 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.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| Monography | Library | C1 90 (Browse shelf) | Available | 107044 |
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.
There are no comments for this item.