Regression Inside Out

Regression Inside Out by Eric W. Schoon, David Melamed, and Ronald L. Breiger

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.

Available now from Cambridge University Press.


Reviews

‘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