Charles M. Judd, Gary H. McClelland, Carey S. Ryan

Data Analysis (eBook, PDF)

A Model Comparison Approach To Regression, ANOVA, and Beyond, Third Edition

• Format: PDF

Produktbeschreibung

Noted for its model-comparison approach and unified framework based on the general linear model (GLM), this classic text provides readers with a greater understanding of a variety of statistical procedures including analysis of variance (ANOVA) and regression.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 378
• Erscheinungstermin: 18. Mai 2017
• Englisch
• ISBN-13: 9781317591214
• Artikelnr.: 48418394

Autorenporträt

Charles "Chick" M. Judd is Professor of Distinction in the College of Arts and Sciences at the University of Colorado at Boulder. His research focuses on social cognition and attitudes, intergroup relations and stereotypes, judgment and decision making, and behavioral science research methods and data analysis.



Gary H. McClelland

is Professor of Psychology at the University of Colorado at Boulder. A Faculty Fellow at the Institute of Cognitive Science, his research interests include judgment and decision making, psychological models of economic behavior, statistics & data analysis, and measurement and scaling.


Carey S. Ryan

is a Professor in the Department of Psychology at the University of Nebraska at Omaha. She has research interests in stereotyping and prejudice, group processes, and program evaluation.

Inhaltsangabe

Preface 1. Introduction to Data Analysis 2. Simple Models: Definitions of
Error and Parameter Estimates 3. Simple Models: Models of Error and
Sampling Distributions 4. Simple Models: Statistical Inferences about
Parameter Values 5. Simple Regression: Estimating Models with a Single
Continuous Predictor 6. Multiple Regression: Models with Multiple
Continuous Predictors 7. Moderated and Nonlinear Regression Models 8.
One-Way ANOVA: Models with a Single Categorical Predictor 9. Factorial
ANOVA: Models with Multiple Categorical Predictors and Product Terms 10.
ANCOVA: Models with Continuous and Categorical Predictors 11.
Repeated-Measures ANOVA: Models with Nonindependent Errors 12.
Incorporating Continuous Predictors with Nonindependent Data: Towards Mixed
Models 13. Outliers and Ill-Mannered Error 14. Logistic Regression:
Dependent Categorical Variables References Appendix Author Index Subject
Index