Seven rules for social research

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書誌事項

Seven rules for social research

Glenn Firebaugh

Princeton University Press, c2008

  • : hardcover
  • : pbk.

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注記

Includes bibliographical references and indexes

内容説明・目次

内容説明

"Seven Rules for Social Research" teaches 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 Research" is 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 are as follows: 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; and, let method be the servant, not the master.

目次

Preface xi Chapter 1: The First Rule There Should Be the Possibility of Surprise in Social Research 1 Selecting a Research Question 2 Researchable Questions 2 Interesting Questions 4 Selecting a Sample 18 Samples in Qualitative Studies 23 Is Meaningful Social Research Possible? 26 Summary 29 Student Exercises on Rule 1 31 Chapter 2: The Second Rule Look for Differences That Make a Difference, and Report Them 36 You Can't Explain a Variable with a Constant 37 Maximizing Variance to Find the Effect of a Cause 39 Size versus Statistical Significance 41 Comparing Effects Where There Is a Common Metric 42 Calibration: Converting Explanatory Variables to a Common Metric 44 Substantive Profiling: The Use of Telling Comparisons 46 Visual Presentation of Results 51 Policy Importance 53 Importance for Theory 54 Conclusion 56 Student Exercises on Rule 2 58 Chapter 3: The Third Rule Build Reality Checks into Your Research 64 Internal Reality Checks 65 Reality Checks on Data?Dubious Values and Incomplete Data 65 Reality Checks on Measures?Aim for Consistency in Conceptualization and Measurement 69 Reality Checks on Models?The Formal Equivalence Check 71 External Reality Checks: Validation with Other Data and Methods 76 Using Causal-Process Observations to Test Plausibility of Results 77 Using Ethnographic Data to Help Interpret Survey Results 79 Other Examples of Multiple-Method Research 81 Concluding Remark 82 Student Exercises on Rule 3 84 Chapter 4: The Fourth Rule Replicate Where Possible 90 Sources of Uncertainty in Social Research 91 Overview: From Population to Sample and Back to Population 93 Measurement Error as a Source of Uncertainty 100 Illustration: Two Methods for Estimating Global Poverty 101 Toward a Solution: Identical Analyses of Parallel Data Sets 105 Meta-analysis: Synthesizing Results Formally across Studies 106 Summary: Your Confidence Intervals Are Too Narrow 109 Student Exercises on Rule 4 111 Chapter 5: The Fifth Rule Compare Like with Like 120 Correlation and Causality 121 Types of Strategies for Comparing Like with Like 129 Matching versus Looking for Differences 130 The Standard Regression Method for Comparing Like with Like 131 Critique of the Standard Linear Regression Strategy 132 Comparing Like with Like Through Fixed-Effects Methods 134 First-Difference Models: Subtracting Out the Effects of Confounding Variables 134 Special Case: Growth-Rate Models 138 Sibling Models 140 Comparing Like with Like through Matching on Measured Variables 146 Exact Matching 146 Propensity-Score Method 147 Matching as a Preprocessing Strategy for Reducing Model Dependence 151 Comparing Like with Like through Naturally Occurring Random Assignment 152 Instrumental Variables: Matching through Partial Random Assignment 153 Matching Through Naturally Occurring Random Assignment to the Treatment Group 158 Comparison of Strategies for Comparing Like with Like 159 Conclusion 162 Student Exercises on Rule 5 165 Chapter 6: The Sixth Rule Use Panel Data to Study Individual Change and Repeated Cross-section Data to Study Social Change 172 Analytic Differences between Panel and Repeated Cross-section Data 173 Three General Questions about Change 175 Changing-Effect Models, Part 1: Two Points in Time 176 Changing-Effect Models, Part 2: Multilevel Models with Time as the Context 182 What We Want to Know 183 The General Multilevel Model 183 Convergence Models 185 The Sign Test for Convergence: Comparing Your fs and ds 186 Convergence Model versus Changing-Effect Model 191 Bridging Individual and Social Change: Estimating Cohort Replacement Effects 195 An Accounting Scheme for Social Change 197 Linear Decomposition Method 198 Summary 201 Student Exercises on Rule 6 203 Chapter 7: The Seventh Rule Let Method Be the Servant, Not the Master 207 Obsession with Regression 209 Naturally Occurring Random Assignment, Again 209 Decomposition Work in the Social Sciences 218 Decomposition of Variance and Inequality 220 Decomposition of Segregation Indexes 222 The Effects of Social Context 226 Context Effects as Objects of Study 227 Context Effects as Nuisance 230 Critical Tests in Social Research 231 Conclusion 235 Student Exercises on Rule 7 236 References 241 Index 253

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