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.
Demonstrates new techniques for interpreting and applying linear statistical analysis 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.
Recenzijas
'A book of wisdom and insight that will lead even seasoned quantitative researchers to have a deeper grasp of their own methods, provides a continual stream of 'ah-ha!' experiences, and a bold argument about how to go forwards. Not to be missed!' John Levi Martin, Professor, Department of Sociology, University of Chicago 'This outstanding book represents a principled way of taking the ideas we're used to and helping us answer the questions we really want to answer - rather than the ones we think we can answer. It brings a deeply sociological lens to a 'basic' tool in a way that will help push substantive thinking in quantitative methods.' James Moody, Robert O. Keohane Professor of Sociology, Duke University 'Regression Inside Out ingeniously takes us under the hood of regression models to show how much more we can learn from them when we think relationally and consider cases and variables as co-constitutive for their outputs. Not only does it elegantly enhance our toolkits, it also brilliantly builds bridges between seemingly disparate methodological approaches. This theoretically deep yet very accessible book is an absolute must-read for anyone conducting regression analysis and for anyone thinking about multi-method research.' Sophie Mützel, Professor of Sociology, University of Lucerne, Switzerland
Papildus informācija
Demonstrates new ways to extract knowledge from statistical data and unlock more nuanced interpretations than has previously been possible.
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.
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. David Melamed is Professor of Sociology and Translational Data Analytics at The Ohio State University. He is currently co-Editor of Sociological Methodology. His research interests include the emergence of stratification and cooperation in complex systems. His work has appeared in American Journal of Sociology, American Sociological Review, and interdisciplinary venues. Ronald L. Breiger is Regents Professor of Sociology at the University of Arizona. His interests include social network theory and methods and measurement issues in cultural and institutional analysis. He is the recipient of distinguished career awards from (respectively) the Methodology and Mathematical Sociology Sections of the American Sociological Association.
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