Multiple Regression and Beyondoffers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods.
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Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling 作者:Keith 出版社:Routledge 出版日期:2025-09-29 語言:英文 規格:平裝 / 676頁 / 普通級/ 初版 |
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Multiple Regression and Beyondoffers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods.
Timothy Z. Keith is Professor Emeritus at the University of Texas, Austin. Before retiring he was director of the graduate school psychology program (now school and clinical child psychology) in the Department of Educational Psychology. His research focused on the nature and measurement of intelligence, including the validity of tests of intelligence and the theories from which they are drawn.
Matthew R. Reynolds is Professor of Educational Psychology at the University of Kansas. His research focuses on the measurement and structure of human cognitive abilities and on sex differences in cognitive abilities and academic achievement. Jacqueline M. Caemmerer is an Assistant Professor in the Department of Educational Psychology (school psychology graduate programs) at the University of Connecticut. Her research interests are in psychological assessment and validity issues. She is interested in better understanding what frequently used tests measure, their predictive validity, and developmental and cultural considerations of tests.
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