Norm O'Rourke, Ph.D., R.Psych., is a clinical psychologist and associate professor with the Interdisciplinary Research in the Mathematical and Computational Sciences (IRMACS) Centre at Simon Fraser University in Burnaby (BC), Canada. He sits on the executive board of the American Psychological Association's Society for Clinical Geropsychology and the National Mental Health Commission of Canada. To date, he has published two governmental reports and seventy peer-reviewed publications in leading gerontology, measurement, and mental health academic journals. As co-applicant, Dr. O’Rourke has been part of teams awarded $4M in research funding, and $1.3M as principal applicant in governmental and foundation funding as team leader.
Larry Hatcher, Ph.D., is a professor of psychology at Saginaw Valley State University in Saginaw, Michigan, where he teaches classes in general psychology, industrial psychology, elementary statistics, advanced statistics, and computer applications in data analysis. The author of several books dealing with statistics and data analysis, Hatcher has taught at the college level since 1984 after earning his doctorate in industrial and organizational psychology from Bowling Green State University in 1983.
Structural equation modeling (SEM) has become one of the most important statistical procedures in the social and behavioral sciences. This easy-to-understand guide makes SEM accessible to all users—even those whose training in statistics is limited or who have never used SAS. It gently guides users through the basics of using SAS and shows how to perform some of the most sophisticated data-analysis procedures used by researchers: exploratory factor analysis, path analysis, confirmatory factor analysis, and structural equation modeling. It shows how to perform analyses with user-friendly PROC CALIS, and offers solutions for problems often encountered in real-world research.
This second edition contains new material on sample-size estimation for path analysis and structural equation modeling. In a single user-friendly volume, students and researchers will find all the information they need in order to master SAS basics before moving on to factor analysis, path analysis, and other advanced statistical procedures.
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