Designing General Linear Models to Test Research Hypotheses
Published on 14. December 2011
Book
Paperback/Softback
494 pages
978-0-7618-5768-6 (ISBN)
Description
The focus of this text is placed on designing General Linear Models (regression models) to test research hypotheses. The authors illustrate and discuss General Linear Models specifically designed to statistically test research hypotheses that deal with the differences among group means, relationships between continuous variables, analysis of covariance, interaction effects, nonlinear relationships, and repeated measures. Many of the chapters contain sections entitled "General Hypothesis" and "Applied Hypothesis." The General Hypothesis sections are designed to provide the readers with "road maps" regarding how to conduct the various analyses presented in the text. The Applied Hypothesis sections illustrate how the various analyses are conducted with Microsoft Excel and SPSS for Windows and how the outputs should be interpreted to test the hypotheses. Throughout the text, the authors stress the importance of designing regression models that precisely reflect the null and research hypotheses.
Reviews / Votes
The book is focused on designing multiple linear regression models to test research hypotheses. Hypotheses are considered that deal with the differences among group means, relationships between covariates, analysis of covariance, interaction effects, nonlinear relationships, and repeated measures. Most of the chapters contain Applied Hypothesis sections aimed to illustrate how analyses are conducted with Microsoft Excel and SPSS for Windows and how the outputs should be interpreted to test the hypotheses. The authors persistently stress the importance of designing regression models that precisely reflect the null and research hypotheses. . . .The book can be quite useful for graduate students and researchers in applied fields. * Zentralblatt MATH *More details
Language
English
Place of publication
Lanham, MD
United States
Target group
Professional and scholarly
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 27 mm
Weight
711 gr
ISBN-13
978-0-7618-5768-6 (9780761857686)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Keith McNeil has taught statistics and research methods since 1967. He has been active in the Special Interest Group of Multiple Linear Regression in the American Educational Research Association since its inception. He has co-authored three other books on GLM, as well as a text on research methods and a text on survey research and writing dissertations with Isadore Newman. McNeil is an emeritus professor at New Mexico State University.
Isadore Newman has taught statistics and research methods since 1970. He has been active in the Special Interest Group of Multiple Linear Regression in the American Educational Research Association since its inception, serving as the editor of its journal for twenty years. He has co-authored seventeen books and book chapters related to research methods, three of which were co-authored with Keith McNeil on GLM, survey research, and writing dissertations. He is a distinguished professor emeritus at Akron University and currently serves as visiting scholar at Florida International University.
John W. Fraas, the Board of Trustees' distinguished professor emeritus, taught statistics at Ashland University in the Schools of Business, Economics, and Education for nearly four decades. While at Ashland University, he was awarded numerous teaching awards including the first Teaching Excellence Award given by the Association of Collegiate Business Schools and Programs. He has published over thirty-five journal articles dealing with applied statistics in the fields of business management, economics, and education. In addition, he authored a text entitled Basic Concepts in Educational Research and its corresponding workbook (University Press of America).
Isadore Newman has taught statistics and research methods since 1970. He has been active in the Special Interest Group of Multiple Linear Regression in the American Educational Research Association since its inception, serving as the editor of its journal for twenty years. He has co-authored seventeen books and book chapters related to research methods, three of which were co-authored with Keith McNeil on GLM, survey research, and writing dissertations. He is a distinguished professor emeritus at Akron University and currently serves as visiting scholar at Florida International University.
John W. Fraas, the Board of Trustees' distinguished professor emeritus, taught statistics at Ashland University in the Schools of Business, Economics, and Education for nearly four decades. While at Ashland University, he was awarded numerous teaching awards including the first Teaching Excellence Award given by the Association of Collegiate Business Schools and Programs. He has published over thirty-five journal articles dealing with applied statistics in the fields of business management, economics, and education. In addition, he authored a text entitled Basic Concepts in Educational Research and its corresponding workbook (University Press of America).
Content
Chapter 1: Introduction to the General Linear Model
Chapter 2: Hypothesis Testing
Chapter 3: Vectors and Vector Operations
Chapter 4: Research Hypotheses Employing Dichotomous Predictor Variables
Chapter 5: Research Hypotheses Employing Continuous Predictor Variables
Chapter 6: Multiple Continuous Predictor Variables
Chapter 7: Interaction
Chapter 8: Statistical Control of Possible Confounding Variables
Chapter 9: Nonlinear Relationships
Chapter 10: Detection of Change
Chapter 11: Dichotomous Criterion Variable
Chapter 12: The Strategy of Research as Viewed from the GLM Approach
Appendixes
References
Index
Authors
Chapter 2: Hypothesis Testing
Chapter 3: Vectors and Vector Operations
Chapter 4: Research Hypotheses Employing Dichotomous Predictor Variables
Chapter 5: Research Hypotheses Employing Continuous Predictor Variables
Chapter 6: Multiple Continuous Predictor Variables
Chapter 7: Interaction
Chapter 8: Statistical Control of Possible Confounding Variables
Chapter 9: Nonlinear Relationships
Chapter 10: Detection of Change
Chapter 11: Dichotomous Criterion Variable
Chapter 12: The Strategy of Research as Viewed from the GLM Approach
Appendixes
References
Index
Authors