Regression Inside Out

Eric W. Schoon; David Melamed; Ronald L. Breiger

doi:10.1017/9781108887205

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This Book has been cited by the following publications. This list is generated based on data provided by Crossref.

Melamed, David Breiger, Ronald L. and Schoon, Eric W. 2024.

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Rönkkö, Mikko Maula, Markku and Wennberg, Karl 2025. Qualitative Comparative Analysis in Entrepreneurship Research. Entrepreneurship Theory and Practice,

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Eric W. Schoon, Ohio State University, David Melamed, Ohio State University, Ronald L. Breiger, University of Arizona

Publisher:: Cambridge University Press
Online publication date:: March 2024
Print publication year:: 2024
Online ISBN:: 9781108887205
DOI:: https://doi.org/10.1017/9781108887205

Subjects:: Research Methods in Politics, Research Methods in Sociology and Criminology, Research Methods In Sociology and Criminology, Qualitative Research Methods, Research Methods In Politics
Series:: Strategies for Social Inquiry

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Regression Inside Out
Eric W. Schoon, David Melamed, Ronald L. Breiger
Online ISBN: 9781108887205

Book DOI: https://doi.org/10.1017/9781108887205
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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.

‘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

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Regression Inside Out

This Book has been cited by the following publications. This list is generated based on data provided by Crossref.

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Contents

Regression Inside Out
pp i-i

Strategies for Social Inquiry - Series page
pp ii-ii

Regression Inside Out - Title page
pp iii-iii

Copyright page
pp iv-iv

Contents
pp v-viii

Figures
pp ix-x

Tables
pp xi-xii

Acknowledgments
pp xiii-xiv

1 - Introduction
pp 1-14

Part I - Turning Regression Inside Out
pp 15-78

2 - OLS Inside Out
pp 17-49

3 - Generalizing Regression Inside Out
pp 50-61

4 - Turning Variance Inside Out (Coauthor: Eunsung Yoon)
pp 62-78

Part II - Action and Interaction
pp 79-124

5 - Action Detection
pp 81-112

6 - Interaction Detection
pp 113-124

Part III - RIO as a Gateway
pp 125-226

7 - RIO as a Gateway to Case Selection
pp 127-171

8 - RIO as a Gateway to Configurational Comparative Analysis
pp 172-201

9 - RIO as a Gateway to Field Theory
pp 202-219

10 - Conclusion
pp 220-226

Appendices
pp 227-253

Appendix A - A Brief Introduction to Matrices and Matrix Multiplication
pp 227-229

Appendix B - Computation of the Singular Value Decomposition (SVD)
pp 230-232

Appendix C - Variance for Binomial and Count Outcomes
pp 233-234

Appendix D - Compositional Effects in Using RIO to Detect Statistical Interactions
pp 235-246

Appendix E - Monte Carlo Simulation Detecting Interactions by Regressing on Rows of P
pp 247-253

References
pp 254-264

Index
pp 265-266

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