Demonstrates new techniques for interpreting and applying linear statistical analysis â the predominant quantitative method in the social and policy sciences. These methods will help advance substantive thinking in quantitative and mixed-method analysis throughout the social sciences and beyond.
Demonstrates new techniques for interpreting and applying linear statistical analysis â the predominant quantitative method in the social and policy sciences. These methods will help advance substantive thinking in quantitative and mixed-method analysis throughout the social sciences and beyond.
Eric W. Schoon is Associate Professor of Sociology at The Ohio State University. His research interests include case-oriented and relational methods, sociological theory, and cultural dimensions of contentious politics. His work has appeared in outlets including American Sociological Review, Journal of Politics, Social Forces, and Social Problems.
Inhaltsangabe
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.
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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