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Rethinking social inquiry : diverse tools, shared standards / edited by Henry E. Brady and David Collier.
Table of contents Available online
View onlineLIBRA H62 .R4646 2004
Available from offsite location
- Format:
- Book
- Language:
- English
- Subjects (All):
- Social sciences--Research.
- Social sciences.
- Social sciences--Methodology.
- Physical Description:
- xx, 362 pages ; 23 cm
- Place of Publication:
- Lanham, MD : Rowman & Littlefield, [2004]
- Summary:
- When it was first published, Designing Social Inquiry, by political scientists Gary King, Robert Keohane, and Sidney Verba, at once struck chords of controversy. As it became one of the best-selling methodology books in memory, it continued to spark debat
- Contents:
- 1. Refocusing the Discussion of Methodology / Henry E. Brady, David Collier, Jason Seawright 3
- Mainstream Quantitative Methods, Qualitative Methods, and Statistical Theory 3
- The Debate on Designing Social Inquiry 5
- DSI's Contribution 5
- Tools and Standards 7
- Toward an Alternative View of Methodology 10
- Critiques of the Quantitative Template 15
- Qualitative Tools 16
- Linking the Quantitative and Qualitative Traditions 18
- Diverse Tools, Shared Standards 19
- 2. The Quest for Standards: King, Keohane, and Verba's Designing Social Inquiry / David Collier, Jason Seawright, Gerardo L. Munck 21
- Scientific Research, Inference, and Assumptions 22
- Scientific Research 22
- Inference 23
- Descriptive Inference 23
- Causal Inference 25
- Making Inferences: Quantitative Tools and Analytic Goals 26
- Causal Homogeneity 29
- Independence of Observations 30
- Conditional Independence 31
- Guidelines: Summarizing DSI's Framework 36
- A. Defining the Research Problem 37
- B. Specifying the Theory 38
- C. Selecting Cases and Observations 38
- D. Descriptive Inference 40
- E. Causal Inference 42
- F. Further Testing and Reformulating the Theory 44
- Anticipating the Discussion of DSI's Framework 44
- I. Areas of Convergence 44
- II. Areas of Divergence 46
- II. Critiques of the Quantitative Template 51
- 3. Doing Good and Doing Better: How Far Does the Quantitative Template Get Us? / Henry E. Brady 53
- Theology versus Homiletics 53
- Descending from the Rhetorical Heights 56
- Explanation and Causality 56
- Measurement 62
- 4. Some Unfulfilled Promises of Quantitative Imperialism / Larry M. Bartels 69
- The Contribution and a Shortcoming 70
- Omissions and an Agenda for Research 71
- Uncertainty 71
- Qualitative Evidence 71
- Measurement Error 72
- Multiplying Observations 73
- 5. How Inference in the Social (but Not the Physical) Sciences Neglects Theoretical Anomaly / Ronald Rogowski 75
- Problemation and Deductive Theorizing 76
- Theory and Anomaly: Some Examples 77
- Lessons 82
- 6. Claiming Too Much: Warnings about Selection Bias / David Collier, James Mahoney, Jason Seawright 85
- Do the Warnings Claim Too Much? 86
- Selecting Extreme Values on the Dependent Variable: Why Is It an Issue? 88
- An Example 89
- Understanding Why Selection Bias Results from Truncation 90
- Selection Bias in Qualitative Research 92
- Cross-Case Analysis and Selection Bias 94
- Within-Case Analysis and Selection Bias 95
- Evaluating the Causal Relationship 96
- Atypical Cases and Overgeneralization 97
- Stern Warnings about No-Variance Designs 99
- Further Observations about Cross-Case and Within-Case Comparison 100
- III. Qualitative Tools 103
- 7. Tools for Qualitative Research / Gerardo L. Munck 105
- Qualitative Methods: A Survey of Tools 107
- Defining the Universe of Cases: Context, Typologies, and Process Tracing 107
- Case Selection: Dilemmas of Increasing the Number of Observations 112
- Measurement and Data Collection 115
- Causal Assessment in Cross-Case and Within-Case Designs 116
- Beyond Strict Hypothesis Testing: Theory Generation, Reformulation, and the Iterated Assessment of Hypotheses 119
- 8. Turning the Tables: How Case-Oriented Research Challenges Variable-Oriented Research / Charles C. Ragin 123
- Constitution of Cases 125
- Study of Uniform Outcomes 128
- Definition of Negative Cases 130
- Examination of Multiple and Conjunctural Causes 133
- Treatment of Nonconforming Cases and "Determinism" 135
- 9. Case Studies and the Limits of the Quantitative Worldview / Timothy J. McKeown 139
- Philosophy of Science and the Logic of Research 140
- DSI's Philosophy of Science 140
- DSI and the Popperian View of Theory 142
- A Single Logic of Research 143
- Is Inference Fundamentally Quantitative? 144
- Making Inferences from One or a Few Cases 146
- Toward a Methodology of Intensive Research: An Alternative Logic for Case Studies 154
- Understanding Existing Research 154
- Cognitive Mapping 155
- Game Theory Applied to Empirical Situations 156
- A "Folk Bayesian" Approach 158
- Heuristics for Theory Construction 162
- Case Selection Heuristics 163
- Thought Experiments and Counterfactuals 163
- Exploiting Feedback from Observation to Design 164
- Identifying Causal Processes Rather than Testing 164
- IV. Linking the Quantitative and Qualitative Traditions 169
- 10. Bridging the Quantitative-Qualitative Divide / Sidney Tarrow 171
- Challenges of Combining Qualitative and Quantitative Data 172
- Tools for Bridging the Divide 173
- Tracing Processes to Interpret Decisions 173
- Systematic and Nonsystematic Variable Discrimination 174
- Framing Qualitative Research within Quantitative Profiles 175
- Putting Qualitative Flesh on Quantitative Bones 176
- Sequencing Quantitative and Qualitative Research 177
- Triangulation 178
- 11. The Importance of Research Design / Gary King, Robert O. Keohane, Sidney Verba 181
- What We Tried to Do 182
- Our Alleged Errors of Omission 186
- Science as a Collective Enterprise 186
- Lijphart: The Case Study That Broke the Pluralist Camel's Back 186
- Allen: Distinguishing History from Social Science 187
- The Perils of Avoiding Selection Bias 188
- Katzenstein: Distinguishing Descriptive Inference from Causal Inference 189
- Bates: How to Identify a Dependent Variable 190
- Triangular Conclusions 191
- V. Diverse Tools, Shared Standards 193
- 12. Critiques, Responses, and Trade-Offs: Drawing Together the Debate / David Collier, Henry E. Brady, Jason Seawright 195
- Critiques and Statistical Responses 196
- Doing Research That Is Important 197
- The Challenge of Promoting Creativity 200
- Innovative Research, Trade-Offs, and DSI's Framework 201
- Conceptualization and Measurement 202
- Critique 203
- Statistical Response 204
- Selection Bias 209
- Critique 210
- Statistical Response 211
- Probabilistic versus Deterministic Models of Causation 213
- The Statistical Responses 220
- Trade-Offs in Research Design 221
- Trade-Offs, Goals, and Tools 221
- Trade-Offs in DSI 224
- Placing Trade-Offs at the Center of Attention 224
- 13. Sources of Leverage in Causal Inference: Toward an Alternative View of Methodology / David Collier, Henry E. Brady, Jason Seawright 229
- Experiments, Quasi-Experiments, Observational Studies, and Inferential Monsters 230
- Mainstream Quantitative Methods versus Statistical Theory 233
- Determinate versus Indeterminate Research Designs 236
- Data Mining versus Specification Searches 238
- Conditional Independence or the Specification Assumption 240
- Four Approaches to the Qualitative versus Quantitative Distinction 244
- Level of Measurement 245
- Size of the N 245
- Statistical Tests 248
- Thick versus Thin Analysis 248
- Drawing Together the Four Criteria 249
- Cases versus Observations 250
- Data-Set Observations versus Causal-Process Observations 252
- Examples of Causal-Process Observations 256
- Implications of Contrasting Types of Observations 258
- Qualitative versus Quantitative 260
- Adding Observations and Adding Variables: Consequences for the N, Degrees of Freedom, and Inferential Leverage 260
- Implications for Research Design 262
- Missing Data 263
- Standard Quantitative Tools versus Careful Analysis of Causal-Process Observations 263
- Conclusion: Drawing Together the Argument 264
- Balancing Methodological Priorities: Technification and the Quest for Shared Standards 266
- Appendix Data-Set Observations versus Causal-Process Observations: The 2000 U.S. Presidential Election / Henry E. Brady 267
- The Option of Regression Analysis 268
- Turning to Causal-Process Observations 269
- Where Did Lott Go Wrong? 270.
- Notes:
- Includes bibliographical references (pages 315-337) and indexes.
- ISBN:
- 0742511251
- 074251126X
- OCLC:
- 54952956
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