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Seven Rules for Social Research

ISBN-10: 0691135673
ISBN-13: 9780691135670
Edition: 2008
Authors: Glenn Firebaugh
List price: $35.00 Buy it from $24.13
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Description: Seven Rules for Social Researchteaches social scientists how to get the most out of their technical skills and tools, providing a resource that fully describes the strategies and concepts no researcher or student of human behavior can do without.   More...

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Book details

List price: $35.00
Copyright year: 2008
Publisher: Princeton University Press
Publication date: 1/23/2008
Binding: Paperback
Pages: 288
Size: 6.00" wide x 9.00" long x 0.75" tall
Weight: 1.056
Language: English

Seven Rules for Social Researchteaches social scientists how to get the most out of their technical skills and tools, providing a resource that fully describes the strategies and concepts no researcher or student of human behavior can do without. Glenn Firebaugh provides indispensable practical guidance for anyone doing research in the social and health sciences today, whether they are undergraduate or graduate students embarking on their first major research projects or seasoned professionals seeking to incorporate new methods into their research. The rules are the basis for discussions of a broad range of issues, from choosing a research question to inferring causal relationships, and are illustrated with applications and case studies from sociology, economics, political science, and related fields. Though geared toward quantitative methods, the rules also work for qualitative research. Seven Rules for Social Researchis ideal for students and researchers who want to take their technical skills to new levels of precision and insight, and for instructors who want a textbook for a second methods course. The Seven Rules There should be the possibility of surprise in social research. Look for differences that make a difference, and report them. Build reality checks into your research. Replicate where possible. Compare like with like. Use panel data to study individual change and repeated cross-section data to study social change. Let method be the servant, not the master.

Glenn Firebaugh is Professor and Chair, Department of Sociology, Pennsylvania State University.

Preface
The First Rule: There Should Be the Possibility of Surprise in Social Research
Selecting a Research Question
Researchable Questions
Interesting Questions
Selecting a Sample
Samples in Qualitative Studies
Is Meaningful Social Research Possible?
Summary
Student Exercises on Rule 1
The Second Rule: Look for Differences That Make a Difference, and Report Them
You Can't Explain a Variable with a Constant
Maximizing Variance to Find the Effect of a Cause
Size versus Statistical Significance
Comparing Effects Where There Is a Common Metric
Calibration: Converting Explanatory Variables to a Common Metric
Substantive Profiling: The Use of Telling Comparisons
Visual Presentation of Results
Policy Importance
Importance for Theory
Conclusion
Student Exercises on Rule 2
The Third Rule: Build Reality Checks into Your Research
Internal Reality Checks
Reality Checks on Data-Dubious Values and Incomplete Data
Reality Checks on Measures-Aim for Consistency in Conceptualization and Measurement
Reality Checks on Models-The Formal Equivalence Check
External Reality Checks: Validation with Other Data and Methods
Using Causal-Process Observations to Test Plausibility of Results
Using Ethnographic Data to Help Interpret Survey Results
Other Examples of Multiple-Method Research
Concluding Remark
Student Exercises on Rule 3
The Fourth Rule: Replicate Where Possible
Sources of Uncertainty in Social Research
Overview: From Population to Sample and Back to Population
Measurement Error as a Source of Uncertainty
Illustration: Two Methods for Estimating Global Poverty
Toward a Solution: Identical Analyses of Parallel Data Sets
Meta-analysis: Synthesizing Results Formally across Studies
Summary: Your Confidence Intervals Are Too Narrow
Student Exercises on Rule 4
The Fifth Rule: Compare Like with Like
Correlation and Causality
Types of Strategies for Comparing Like with Like
Matching versus Looking for Differences
The Standard Regression Method for Comparing Like with Like
Critique of the Standard Linear Regression Strategy
Comparing Like with Like Through Fixed-Effects Methods
First-Difference Models: Subtracting Out the Effects of Confounding Variables
Special Case: Growth-Rate Models
Sibling Models
Comparing Like with Like through Matching on Measured Variables
Exact Matching
Propensity-Score Method
Matching as a Preprocessing Strategy for Reducing Model Dependence
Comparing Like with Like through Naturally Occurring Random Assignment
Instrumental Variables: Matching through Partial Random Assignment
Matching Through Naturally Occurring Random Assignment to the Treatment Group
Comparison of Strategies for Comparing Like with Like
Conclusion
Student Exercises on Rule 5
The Sixth Rule: Use Panel Data to Study Individual Change and Repeated Cross-section Data to Study Social Change
Analytic Differences between Panel and Repeated Cross-section Data
Three General Questions about Change
Changing-Effect Models, Part 1: Two Points in Time
Changing-Effect Models, Part 2: Multilevel Models with Time as the Context
What We Want to Know
The General Multilevel Model
Convergence Models
The Sign Test for Convergence: Comparing Your [phi]s and [delta]s
Convergence Model versus Changing-Effect Model
Bridging Individual and Social Change: Estimating Cohort Replacement Effects
An Accounting Scheme for Social Change
Linear Decomposition Method
Summary
Student Exercises on Rule 6
The Seventh Rule: Let Method Be the Servant, Not the Master
Obsession with Regression
Naturally Occurring Random Assignment, Again
Decomposition Work in the Social Sciences
Decomposition of Variance and Inequality
Decomposition of Segregation Indexes
The Effects of Social Context
Context Effects as Objects of Study
Context Effects as Nuisance
Critical Tests in Social Research
Conclusion
Student Exercises on Rule 7
References
Index

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