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Theory-Based Data Analysis for the Social Sciences
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Theory-Based Data Analysis for the Social Sciences

Second Edition


February 2013 | 472 pages | SAGE Publications, Inc
This book presents a method for bringing data analysis and statistical technique into line with theory. The author begins by describing the elaboration model for analyzing the empirical association between variables. She then introduces a new concept into this model, the focal relationship. Building upon the focal relationship as the cornerstone for all subsequent analysis, two analytic strategies are developed to establish its internal validity: an exclusionary strategy to eliminate alternative explanations, and an inclusive strategy which looks at the interconnected set of relationships predicted by theory. Using real examples of social research, the author demonstrates the use of this approach for two common forms of analysis, multiple linear regression and logistic regression. Whether learning data analysis for the first time or adding new techniques to your repertoire, this book provides an excellent basis for theory-based data analysis.
 
Preface
 
Acknowledgments
 
About the Author
 
Part I. Conceptual Foundations of the Elaboration Model
 
Chapter 1. Introduction to Theory-Based Data Analysis
 
Chapter 2. The Logic of Theory-Based Data Analysis
 
Chapter 3. Relationships as Associations
 
Chapter 4. The Focal Relationship: Causal Inference
 
Part II. Regression with Simple Random Samples and Complex Samples
 
Chapter 5. The Elaboration Model With Multiple Linear Regression
 
Chapter 6. Regression With Survey Data From Complex Samples
 
Part III. The Elaboration Model With Multiple Linear Regression
 
Chapter 7. Ruling Out Alternative Explanations: Spuriousness and Control Variables
 
Chapter 8. Ruling Out Alternative Theoretical Explanations: Rival Independent Variables
 
Chapter 9. Elaborating the Focal Relationship: Mediation and Intervening Variables
 
Chapter 10. Elaborating the Focal Relationship: Antecedent and Consequent Variables
 
Chapter 11. Specifying Conditions of Influence: Moderating Variables
 
Part IV. The Elaboration Model With Logistic Regression
 
Chapter 12. The Elaboration Model With Logistic Regression
 
Part V. Conclusion
 
Chapter 13. Synthesis and Comments
 
Glossary
 
References
 
Abbreviations
 
Index

“In clear and accessible prose, this book presents a compelling logic for the analysis of non-experimental data. In the process, it clarifies the concepts of statistical association, confounding, and statistical control, and it provides really compelling elaboration schemes to make substantive, rather than purely statistical, sense of it all. It also provides a means for making causal assertions when the criteria of association, causal priority, non-spuriousness, and theoretical rationale are met.”

Robert Bickel
Marshall University

“This text does a superb job of explaining critical concepts such as mediation, moderation, spuriousness, and control variable, using graphic illustrations as well as published articles as examples. I think the illustrated examples are really helpful for illuminating these concepts. Furthermore, the majority of empirical research in the social behavioral sciences utilizes regression, logistic regression, and path analysis. The book discusses many empirical articles utilizing these analytic approaches as examples. Thus, the contents of this book are highly relevant and understandable for those in early stages of research training.”

Eun Young Mun
Rutgers, The State University of New Jersey

I think this is a very much awaited book. I think it is very well suited for PG level, particularly for those MA students who are writing their dissertations (and PhD students as well). As strange as it may seem, students struggle to understand what theory is and how it relates to data. For me this book engages comprehensively in these questions. There is a good discussion of how to work with variables, about the construction of associations and causalities. I wish I could teach more of this book in my MA course, but due to time constraints I would definitely recommend Chapter 1-4 (where the focus is on conceptual discussion). The book is very helpful for those constructing and designing their research. The book is not the ‘beginner level’. It would be helpful if students already have some background in quantitative analysis, therefore I would not, however, recommend for BA level.

Maria Karepova
University of East London Business School

I think this is a very much awaited book. I think it is very well suited for PG level, particularly for those MA students who are writing their dissertations (and PhD students as well). Students often struggle to understand what theory is and how it relates to data. For me this book engages comprehensively in these questions. There is a good discussion of how to work with variables, about the construction of associations and causalities. I wish I could teach more of this book in my MA course, but due to time constraints I would definitely recommend Chapter 1-4 (where the focus is on conceptual discussion). The book is very helpful for those constructing and designing their research project. The book is not a ‘beginner level’ though. It would be helpful for students who already have some background in quantitative analysis, therefore I would not, however, recommend for BA level.

Dr Maria Adamson
Business School, University of East London
January 22, 2014

The prose is too dense for the typical master's degree student. Probably suitable for doctoral students.

Dr Melvin Musick, EdD
Education Dept, Pepperdine University Graduate School of Education/ Psychology - West Los Angeles
September 10, 2013

This will be my first year using the second edition. I have used tthe first edition for several years. I am a bit concerned that the second edition will overlap with DeVellis. This book has been ordered for Fall 2013

Cynthia Gross
Pharmacy Dept, University of Minnesota - Twin Cities
August 8, 2013

Wonderful Text... Dr. Aneshensel makes multivariate analysis sensible and connected to theoretical propositions in a way I have not seen before.

Professor Chris Francovich
Other, Gonzaga University
March 7, 2013

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CH 1

CH 6


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