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Theory-Based Data Analysis for the Social Sciences

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


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

Establishing Relatedness: The "Third Variable"

Association and Causality


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


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


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

Analytic Models For Redundancy

Control Versus Independent Variable


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


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


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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