
Theory-Based Data Analysis for the Social Sciences
Carol S. Aneshensel(Author)
SAGE Publications Inc (Publisher)
1st Edition
Published on 27. March 2002
Book
Paperback/Softback
280 pages
978-0-7619-8736-9 (ISBN)
Article exhausted; check for reprint
Description
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.
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.
More details
Series
Language
English
Place of publication
Thousand Oaks
United States
Target group
College/higher education
Dimensions
Height: 229 mm
Width: 152 mm
Weight
369 gr
ISBN-13
978-0-7619-8736-9 (9780761987369)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
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Theory-Based Data Analysis for the Social Sciences
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Person
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 received awards for distinguished contributions from the Sociology of Mental Health and Medical Sociology sections of the American Sociological Association (ASA). Theory-Based Data Analysis for the Social Sciences received Honorable Mention for Best Publication in 2003 from the Sociology of Mental Health section, ASA.
Content
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
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