|aReading and understanding more multivariate statistics /|cedited by Laurence G. Grimm and Paul R. Yarnold.
|aWashington, DC :|bAmerican Psychological Association,|cc2000.
|axiii, 437 p. :|bill. ;|c26 cm.
|aIncludes bibliographical references and index.
|tIntroduction to multivariate statistics /|rLaurence G. Grimm and Paul R. Yarnold --|tReliability and generalizability theory /|rMichael J. Strube --|tItem response theory /|rDavid H. Henard --|tAssessing the validity of measurement /|rFred B. Bryant --|tCluster analysis /|rJoseph F. Hair, Jr., and William C. Black --|tQ-technique factor analysis : one variation on the two-mode factor analysis of variables /|rBruce Thompson.
|tStructural equation modeling /|rLaura Klem --|tTen commandments of structural equation modeling ;|tCanonical correlation analysis /|rBruce Thompson --|tRepeated measures analyses : ANOVA, MANOVA, and HLM /|rKevin P. Weinfurt --|tSurvival analysis /|rRaymond E. Wright.
|a"In Reading and Understanding MORE Multivariate Statistics, Laurence G. Grimm and Paul R. Yarnold have responded to reader requests to provide the same accessible approach to a new group of multivariate techniques and to related topics in measurement. Chapters demystify the use of cluster analysis, Q-technique factor analysis, structural equation modeling, canonical correlation analysis, repeated measures analysis, and survival analysis. As with the previous volume, chapter authors describe the research questions for which the analysis is most appropriate, the underlying assumptions and rationale of the analysis, and the logic behind interpreting the results. Whether you are a graduate student, researcher, or consumer of research, this volume is guaranteed to increase your comfort level and confidence in reading and understanding multivariate statistics."--BOOK JACKET.