Kooperativer Bibliotheksverbund

UID:

Format: 1 online resource (xxvii, 583 pages) : , digital, PDF file(s).

Edition: First edition.

ISBN: 9781108265690 , 1108265693 , 9781108271158 , 1108271154 , 9781108241762 , 110824176X

Series Statement: Methodological tools in the social sciences

Content: The radical interdependence between humans who live together makes virtually all human behavior conditional. The behavior of individuals is conditional upon the expectations of those around them, and those expectations are conditional upon the rules (institutions) and norms (culture) constructed to monitor, reward, and punish different behaviors. As a result, nearly all hypotheses about humans are conditional - conditional upon the resources they possess, the institutions they inhabit, or the cultural practices that tell them how to behave. Interaction Models provides a stand-alone, accessible overview of how interaction models, which are frequently used across the social and natural sciences, capture the intuition behind conditional claims and context dependence. It also addresses the simple specification and interpretation errors that are, unfortunately, commonplace. By providing a comprehensive and unified introduction to the use and critical evaluation of interaction models, this book shows how they can be used to test theoretically-derived claims of conditionality.

Note: Title from publisher's bibliographic system (viewed on 03 Nov 2023). , Cover -- Half-title -- Series information -- Title page -- Imprints page -- Dedication -- Contents -- List of Figures -- List of Tables -- Preface -- Acknowledgments -- 1 Introduction -- 1.1 Resource Endowments -- 1.2 Institutions -- 1.3 Culture/Identity -- 1.4 Plan of the Book -- Part I The Fundamentals -- 2 Theories and Their Conditional Implications -- 2.1 How Do I Know When My Theory Posits a Conditional Relationship? -- 2.2 The Difference between Moderation and Mediation -- 2.3 How Does a Multiplicative Term Capture Conditionality? -- 2.4 Moving beyond the Interaction Effect -- 2.5 The Symmetry of Interaction and Its Implications for Theory Testing -- 2.6 Five Key Predictions -- 2.7 Exercises -- 3 Interaction Model Specification -- 3.1 Include All Constitutive Terms -- 3.2 Why Is It Important to Include All of the Constitutive Terms? -- 3.2.1 Multicollinearity -- 3.3 An Alternative Model Specification When One of the Modifying Variables is Discrete -- 3.3.1 Can I Just Split My Sample? -- 3.4 A Different Alternative Model Specification when Both Modifying Variables are Discrete -- 3.5 Exercises -- 4 Interpreting Quantities of Interest -- 4.1 Think about Effects in terms of Derivatives and Differences -- 4.2 Calculate Appropriate Measures of Uncertainty -- 4.2.1 Effects and Measures of Uncertainty -- 4.2.2 Predicted Values and Measures of Uncertainty -- 4.2.3 Substantive Significance -- 4.3 Key Quantities of Interest and Some Prototypical Results -- 4.4 Exercises -- 5 Three Substantive Applications -- 5.1 When X and Z are Both Discrete: Gender, Race, and Support for the Republican Party -- 5.2 When X is Continuous and Z is Discrete: Ideology, Race, and Support for Barack Obama -- 5.3 When X and Z Are Both Continuous: Demand and Supply Effects on Women's Legislative Representation -- 5.4 Exercises -- Part II More Complex Forms of Conditionality. , 6 When We Have More Than One Modifying Variable -- 6.1 When the Modifying Effects of Z and W are Independent -- 6.1.1 Substantive Application: Gender, Education, Age, and Support for Feminism -- 6.2 When the Modifying Effects of Z and W are Dependent -- 6.2.1 An Alternative Interaction Model When the Modifying Variables are All Discrete -- 6.2.2 Substantive Application: The Impact of Demand, Supply, and Regime Type on Women's Legislative Representation -- 6.3 Exercises -- 7 When an Independent Variable Interacts with Itself -- 7.1 Polynomial Regression Models -- 7.1.1 Substantive Application: The Impact of Party Ideology on Campaign Sentiment -- 7.1.2 Using Polynomial Regression to Model Non-linear Interaction Effects -- 7.2 Possible Threshold Effects -- 7.2.1 Piecewise Linear Regression Models -- 7.2.2 Switching Regression Models -- 7.3 Exercises -- Part III Interactions and Limited Dependent Variables -- 8 Interactions and Dichotomous Dependent Variables -- 8.1 The Linear Probability Model -- 8.2 The Basis for Logit and Probit Models -- 8.2.1 The Pure Probability Approach -- 8.2.2 The Latent Variable Approach -- 8.2.3 The Random Utility Approach -- 8.3 Interpretation and Interaction Effects in "Additive" Logit and Probit Models -- 8.3.1 Coefficients -- 8.3.2 Marginal Effects on Probabilities -- 8.3.3 Predicted Probabilities -- 8.3.4 Differences in Predicted Probabilities -- 8.3.5 Odds Ratios -- 8.3.6 Interaction Effects -- 8.4 Interpretation and Interaction Effects in "Interactive" Logit and Probit Models -- 8.4.1 Coefficients -- 8.4.2 Marginal Effects on Probabilities -- 8.4.3 Predicted Probabilities -- 8.4.4 Differences in Predicted Probabilities -- 8.4.5 Odds Ratios -- 8.4.6 Interaction Effects -- 8.5 Measures of Uncertainty -- 8.5.1 The Method of Simulated Coefficients -- 8.5.2 The Bootstrap Method -- 8.5.3 The Delta Method. , 8.6 Substantive Application: Determinants of Pre-electoral Coalition Formation -- 8.7 Exercises -- 9 Interactions and Ordered Dependent Variables -- 9.1 A Latent Variable Approach -- 9.2 Interpretation -- 9.2.1 Coefficients -- 9.2.2 Marginal Effects on Probabilities -- 9.2.3 Differences in Predicted Probabilities -- 9.2.4 Odds Ratios -- 9.2.5 Interaction Effects -- 9.3 Substantive Application: Ideology, Race, and Presidential Approval of Barack Obama -- 9.4 Exercises -- 10 Interactions and Unordered Dependent Variables -- 10.1 A Random Utility Approach -- 10.2 Data Structure and Interactions -- 10.3 Interpretation -- 10.3.1 Coefficients -- 10.3.2 Marginal Effects on Probabilities -- 10.3.3 Differences in Predicted Probabilities -- 10.3.4 Odds Ratios -- 10.3.5 Interaction Effects -- 10.4 Substantive Application: Policy Preferences, Gender, and Party Support in the 1992 UK Elections -- 10.5 Exercises -- Appendix A Basic Properties of Variances -- Appendix B Marginal Effects and Variances for Various Linear-Interactive Models -- Appendix C Calculating the Smallest Standard Error for the Marginal Effect of X on Y -- Appendix D Calculating the Values of the Modifying Variable Z at which the Bounds of the Confidence Interval for the Marginal Effect of X Equal 0 -- D.1 Substantive Example: Marginal Effect Plot for Demand -- References -- Solutions -- Alphabetical Index.

Additional Edition: ISBN 9781108416719

Additional Edition: ISBN 1108416713

Language: English