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Designing General Linear Models to Test Research Hypotheses
Designing General Linear Models to Test Research Hypotheses
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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.
Table of Contents
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
Product details
| Published | Dec 14 2011 |
|---|---|
| Format | Paperback |
| Edition | 1st |
| Extent | 494 |
| ISBN | 9780761857686 |
| Imprint | University Press of America |
| Dimensions | 9 x 6 inches |
| Publisher | Bloomsbury Publishing |
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