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Handbook of applied multivariate statistics and mathematical modeling

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Handbook of applied multivariate statistics and mathematical modeling/ edited by Howard E.A. Tinsley, Steven D. Brown.
其他作者:	Brown, Steven D.
出版者:	San Diego :Academic Press, : c2000.,
面頁冊數:	xxviii, 721 p. :ill. ;24 cm.
內容註:	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.
內容註:	Multivariate statistics and mathematical modeling / Howard E.A. Tinsley and Steven D. Brown -- Role of theory and experimental design in multivariate analysis and mathematical modeling/ John Hetherington -- Scale construction and psychometric considerations / Rene V. Dawis -- Interrater reliability and agreement / Howard E.A. Tinsley and David J. Weiss -- Interpreting and reporting results/ Mark Hallahan and Robert Rosenthal -- Issues in the use and application of multiple regression analysis / Anre Venter and Scott E. Maxwell -- Multivariate analysis of variance and covariance/ Carl J Huberty and Martha D. Petoskey -- Discriminant analysis / Michael T. Brown and Lori R. Wicker -- Canonical correlation analysis / Robert M. Thorndike -- Exploratory factor analysis / Robert Cudeck -- Cluster analysis/ Paul A. Gore, Jr. -- Multidimensional scaling / Mark L. Davison and Stephen G. Sireci -- Time-series designs and analyses/ Melvin M. Mark, Charles S. Reichardt, and Lawrence J. Sanna -- Poisson regression, logistic regression, and loglinear models for random counts / Peter B. Imrey -- Structural equation modeling : uses and issues/ Lisabeth F. Dilalla --Confirmatory factor analysis / Rick H. Hoyle -- Multivariate meta-analysis / Betsy J. Becker -- Generalizability theory / George A. Marcoulides -- Item response models for the analysis of educational and psychological test data/ Ronald K. Hambleton, Frederic Robin, and Dehui Xing -- Multitrait-multimethod analysis / Levent Dumenci -- Using random coefficient linear models for the analysis of hierarchically nested data / Ita G.G. Kreft -- Analysis of circumplex models/ Terence J.G. Tracey -- Using covariance structure analysis to model change over time / John B. Willett and Margaret K. Keiley.
標題:	Mathematical models. -
電子資源:	http://www.sciencedirect.com/science/book/9780126913606An electronic book accessible through the World Wide Web; click for information
電子資源:	http://www.loc.gov/catdir/toc/els033/99068685.html
電子資源:	http://www.loc.gov/catdir/description/els033/99068685.html
ISBN:	0126913609

Handbook of applied multivariate statistics and mathematical modeling
Handbook of applied multivariate statistics and mathematical modeling[electronic resource] /edited by Howard E.A. Tinsley, Steven D. Brown. - San Diego :Academic Press,c2000. - xxviii, 721 p. :ill. ;24 cm.

Includes bibliographical references and indexes.

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.

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.

Electronic reproduction.
Amsterdam :
Elsevier Science & Technology,
2007.

Mode of access: World Wide Web.

ISBN: 0126913609

Source: 78927:78927Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:

522882
Mathematical models.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QA278 / .H3453 2000eb

Dewey Class. No.: 519.535

Handbook of applied multivariate statistics and mathematical modeling
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245 0 0 $a Handbook of applied multivariate statistics and mathematical modeling $h [electronic resource] / $c edited by Howard E.A. Tinsley, Steven D. Brown.
260 $a San Diego : $c c2000. $b Academic Press,
300 $a xxviii, 721 p. : $b ill. ; $c 24 cm.
504 $a Includes bibliographical references and indexes.
505 0 $a 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.
505 0 $a Multivariate statistics and mathematical modeling / Howard E.A. Tinsley and Steven D. Brown -- Role of theory and experimental design in multivariate analysis and mathematical modeling/ John Hetherington -- Scale construction and psychometric considerations / Rene V. Dawis -- Interrater reliability and agreement / Howard E.A. Tinsley and David J. Weiss -- Interpreting and reporting results/ Mark Hallahan and Robert Rosenthal -- Issues in the use and application of multiple regression analysis / Anre Venter and Scott E. Maxwell -- Multivariate analysis of variance and covariance/ Carl J Huberty and Martha D. Petoskey -- Discriminant analysis / Michael T. Brown and Lori R. Wicker -- Canonical correlation analysis / Robert M. Thorndike -- Exploratory factor analysis / Robert Cudeck -- Cluster analysis/ Paul A. Gore, Jr. -- Multidimensional scaling / Mark L. Davison and Stephen G. Sireci -- Time-series designs and analyses/ Melvin M. Mark, Charles S. Reichardt, and Lawrence J. Sanna -- Poisson regression, logistic regression, and loglinear models for random counts / Peter B. Imrey -- Structural equation modeling : uses and issues/ Lisabeth F. Dilalla --Confirmatory factor analysis / Rick H. Hoyle -- Multivariate meta-analysis / Betsy J. Becker -- Generalizability theory / George A. Marcoulides -- Item response models for the analysis of educational and psychological test data/ Ronald K. Hambleton, Frederic Robin, and Dehui Xing -- Multitrait-multimethod analysis / Levent Dumenci -- Using random coefficient linear models for the analysis of hierarchically nested data / Ita G.G. Kreft -- Analysis of circumplex models/ Terence J.G. Tracey -- Using covariance structure analysis to model change over time / John B. Willett and Margaret K. Keiley.
520 $a 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.
533 $a Electronic reproduction. $b Amsterdam : $c Elsevier Science & Technology, $d 2007. $n Mode of access: World Wide Web. $n System requirements: Web browser. $n Title from title screen (viewed on Aug. 2, 2007). $n Access may be restricted to users at subscribing institutions.
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856 4 1 $3 Table of contents $u http://www.loc.gov/catdir/toc/els033/99068685.html
856 4 2 $3 Publisher description $u http://www.loc.gov/catdir/description/els033/99068685.html
994 $a C0 $b TEF