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



280 pages | SAGE Publications, Inc
The advent of complex and powerful computer-generated statistical models has greatly eroded the former prominence of social theory in data analysis, replacing it with an emphasis on statistical technique. To correct this trend, Carol S Aneshensel presents a method for bringing data analysis and statistical technique into line with theory. She approaches this task by first providing an overview that explains the connection between data analysis, statistical technique and theory. This section includes a description of the elaboration model for analyzing the empirical association between two variables by adding a `third variable' to the analysis.

The author then introduces a new concept into this model, the focal relationship. This concept is the one cause-and-effect type of relationship of primary significance that is indispensable to the entire theory. 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 for the focal relationship using control and other independent variables to rule out spuriousness and redundancy, respectively; and,

- An inclusive strategy to demonstrate that the focal relationship fits within an interconnected set of relationships predicted by theory using antecedent, intervening and consequent variables.

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.

 
Chapter 1: Introduction to Theory-Based Data Analysis
The Connection Between Analysis, Theory and Statistics

 
Elements of Theory-Based Analysis

 
The Inherent Subjectivity of Analysis

 
Looking Ahead

 
 
Chapter 2: The Logic of Theory-Based Data Analysis
Inductive and Deductive Processes

 
Operationalization and The Assessment of Fit

 
The Roundabout Route of Failing to Reject

 
Summary

 
 
Chapter 3: Associations and Relationships
Association: The Basic Building Block

 
Establishing Relatedness: The "Third Variable"

 
Association and Causality

 
Summary

 
 
Chapter 4: The Focal Relationship: Demonstrating Internal Validity
Coincident Associations: The Exclusionary "Third Variable"

 
Causal Connections: The Inclusive "Third Variable"

 
An Example of Exclusionary and Inclusive "Third Variables"

 
Explaining Y Versus the Focal Relationship

 
Summary

 
 
Chapter 5: Ruling Out Alternative Explanations: Spuriousness and Control Variables
Spuriousness: The Illusion of Relationship

 
The Analysis of Simple Spuriousness

 
Complex Sources of Spuriousness

 
The Analysis of Complex Spuriousness

 
Death Looms on the Horizon: An Example of Partial Spuriousness

 
Summary

 
 
Chapter 6: Ruling Out Alternative Theoretical Explanations: Additional Independent Variables
Redundancy: Alternative Theories

 
Analytic Models For Redundancy

 
Control Versus Independent Variable

 
Summary

 
 
Chapter 7: Elaborating an Explanation: Antecedent, Intervening, and Consequent Variables
Intervening Variables: The Causal Mechanism

 
The Analysis of Intervening Variables

 
Mediation Illustrated: Explaining the Intergenerational Transmission of Divorce

 
Antecedent and Consequent Variables

 
Antecedent and Consequent Variables Illustrated: Divorce and Intergenerational Family Relations

 
Summary

 
 
Chapter 8: Specifying Conditions of Influence: Effect Modification and Subgroup Variation
Conditional Relationships

 
Conditional Relationships as Interactions

 
Subgroup Analysis of Conditional Relationships

 
Subgroup Versus Interaction Analysis

 
Considerations in the Selection of Moderating Variables

 
Summary

 
 
Chapter 9: Synthesis and Commentary
A Recap of Theory-Based Data Analysis

 
Informative Comparisons

 
Imperfect Knowledge

 

An excellent effort by Carol to bridge the statistical technicalities and theoretical explanation in the social research playing field. Easy to understand even for non-statistic savvy readers.

Mr Mohamad Ghazali
school of accountancy, University Utara Malaysia
August 5, 2013

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Carol S. Aneshensel

Carol S. Aneshensel is a sociologist (Ph.D., Cornell University) and Professor at the University of California, Los Angeles. She specializes in the fields of the sociology of mental health and medical sociology, with an emphasis on the social origins of stress and its impact on depression. She has been Principal Investigator for numerous studies funded by the National Institute on Aging and the National Institute of Mental Health. She has published more than 75 peer-review journal articles and several books, including her work as lead editor of the Handbook of the Sociology of Mental Health, Second Edition (Springer, 2012). She has... More About Author

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