This revised edition of the text has been updated with such changes as: coverage of both exploratory and confirmatory factor analysis plus illustrations of LISREL and EQS; inclusion of the relatively new EXAMINE procedure from SPSSX - a program for exploring data; a new section on the doubly multivariate problem in which subjects are measured on several dependent outcome variables at each point in time, or for each treatment/condition; and added exercises on categorical data analysis and the answers for the more difficult problems. There is a 3.5" disk (free to those adopting the text) of all data sets in the book, along with several large data sets.
"synopsis" may belong to another edition of this title.
"In summary, this book will appeal to graduate students in a variety of disciplines including psychology, education, business, and management. It is an excellent text that could be used in courses on multivariate analysis that are targeted toward students who probably do not have a Master's degree in mathematics or statistics...Topics are explained clearly and the examples and explanations of results make the techniques described therein understandable. I particularly appreciated the emphasis on power, evaluation of assumptions, cross-validation, and concerns about capitalization on chance."
—Organizational Research Methods
"The book is sprinkled with practical advice that researchers will find useful when applying these techniques to their work....Beginning users of multivariate statistics will appreciate the detailed examples from the social-science literature that include annotated output....Stevens does an excellent job of conveying how multivariate statistics is currently performed in the social sciences, with advice along the way on how to improve the status quo."
—The American Statistician
"...Dr. Stevens writes so clearly. My students tell me in unsolicited comments that his text is helpful in developing their understanding. The material is presented in an informative and engaging manner."
—Gary J. Lautenschlager
University of Georgia
"The liberal inclusion of data examples using such packages as SAS and SPSS is especially helpful to the students."
—Daniel D. Blaine
University of Hawaii at Manoa
University of Cincinnati
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