Preface
R Duncan Luce: Foreword
Part I. The Limitations of Descriptive Methodology
1: Why Social Sciences Are Not Scientific Enough
2: Can Social Science Approaches Find the Law of Gravitation?
3: How to Construct Predictive Models: Simplicity and Non-Absurdity
4: Example of Model Building: Electoral Volatility
5: Physicists Multiply, Social Scientists Add―Even when It Doesn't Add up
6: All Hypotheses Are Not Created Equal
7: Why Most Numbers Published in Social Sciences Are Dead on Arrival
Part II. Quantitatively Predictive Logical Models
8: Forbidden Areas and Anchor Points
9: Geometric Means and Lognormal Distributions
10: Example of Interlocking Models: Party Sizes and Cabinet Duration
11: Beyond Constraint-Based Models: Communication Channels and Growth Rates
12: Why We Should Shift to Symmetric Regression
13: All Indices Are Not Created Equal
Part III. Synthesis of Predictive and Descriptive Approaches
14: From Descriptive to Predictive Approaches
15: Recommendations for Better Regression
16: Converting from Descriptive Analysis to Predictive Models
17: Are Electoral Studies a Rosetta Stone for Parts of Social Sciences?
18: Beyond Regression: The Need for Predictive Models
References
Index
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