Description
Linear regression analysis, with its many generalizations, is the predominant quantitative method used throughout the social sciences and beyond. The goal of the method is to study relations among variables. In this book, Schoon, Melamed and Breiger turn regression modeling inside out to put the emphasis on the cases (people, organizations, and nations) that comprise the variables. By re-analyzing influential published research, they reveal new insights and present a principled way to unlock a set of more nuanced interpretations than has previously been attainable. The emphasis is on intuition and examples that can be reproduced using the code and datasets provided. Relating their contributions to methodologies that operate under quite different philosophical assumptions, the authors advance multi-method social science and help to bridge the divide between quantitative and qualitative research. The result is a modern, accessible, and innovative take on extracting knowledge from data.
Table of Contents
1. Regression inside out; Part I: 2. OLS inside out; 3. Generalizing regression inside out; 4. Turning variance inside out with Eunsung Yoon; Part II: 5. Action detection; 6. Interaction detection; Part III: 7. RIO as a gateway to case selection; 8. RIO as a gateway to configurational comparative analysis; 9. RIO as a gateway to field theory; 10. Conclusion; Appendix A: A brief introduction to matrices and matrix multiplication; Appendix B: Computation of the singular value decomposition (SVD); Appendix C: Variance for binomial and count outcomes; Appendix D: Compositional effects in using RIO to detect statistical interactions; Appendix E: Monte Carlo simulation detecting interactions by regressing on rows of P.
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