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| HANDBOOK OF APPLIED MULTIVARIATE STATISTICS AND MATHEMATICAL MODELING
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Edited By
Howard Tinsley, University of Florida, Gainesville, U.S.A.
Steven Brown, Loyola University of Chicago, Wilmette, Illinois, U.S.A.
Description
Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many
practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep
abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the
appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers
to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook
emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish
which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate
statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences
as well as the humanities.
Audience
Scientific researchers, academics, and research professionals in applied settings in the biological and social sciences
Contents
Introduction.H.E.A. Tinsley and S.D. Brown, Multivariate Statistics and Mathematical Modeling.J. Hetherington, Role
of Theory and Experimental Design in Multivariate Analysis and Mathematical Modeling.R.V. Dawis, Scale Construction and Psychometric
Considerations.H.E.A. Tinsley and D.J. Weiss, Interrater Reliability and Agreement.M. Hallahan and R. Rosenthal,
Interpreting and Reporting Results.A. Venter and S.E. Maxwell, Issues in the Use and Application of Multiple Regression Analysis.
C.J. Huberty and M.D. Petoskey, Multivariate Analysis of Variance and Covariance.M.T. Brown and L.R. Wicker, Discriminant
Analysis.R.M. Thorndike, Canonical Correlation Analysis.R. Cudeck, Exploratory Factor Analysis.P.A. Gore, Jr.,
Cluster Analysis.M.L. Davison and S.G. Sireci, Multidimensional Scaling.M.M. Mark, C.S. Reichardt, and L.J. Sanna,
Time-Series Designs and Analyses.P.B. Imrey, Poisson Regression, Logistic Regression, and Loglinear Models for Random Counts.
L.F. Dilalla, Structural Equation Modeling: Uses and Issues.R.H. Hoyle, Confirmatory Factor Analysis.B.J. Becker,
Multivariate Meta-analysis.G.A. Marcoulides, Generalizability Theory.R.K. Hambelton, F. Robin, and D. Xing, Item
Response Models for the Analysis of Educational and Psychological Test Data.L. Dumenci, Multitrait-Multimethod Analysis.I.G.G.
Kreft, Using Random Coefficient Linear Models for the Analysis of Hierarchically Nested Data.T.J.G. Tracey, Analysis of
Circumplex Models.J.B. Willett and M.K. Keiley, Using Covariance Structure Analysis to Model Change over Time.
Author Index.
Subject Index.
| Bibliographic details |
Hardbound, 721 pages, publication date: APR-2000
ISBN-13: 978-0-12-691360-6
ISBN-10: 0-12-691360-9
Imprint: ACADEMIC PRESS
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| Price and Ordering |
Price:
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USD 225
EUR 160.95
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095/953
Last update: 4 Sep 2009
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