• Summary
  • Contents
  • Subject index

‘The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articles on topics of central importance to quantitative social research, many written by leaders in the field. Everyone engaged in statistical analysis of social-science data will find something of interest in this book.’

- John Fox, Professor, Department of Sociology, McMaster University

‘The authors do a great job in explaining the various statistical methods in a clear and simple way - focussing on fundamental understanding, interpretation of results, and practical application - yet being precise in their exposition.’

- Ben Jann, Executive Director, Institute of Sociology, University of Bern

‘Best and Wolf have put together a powerful collection, especially valuable in its separate discussions of uses for ...

Logistic Regression
Logistic regression
HenningBest and ChristofWolf
Introduction

Many questions raised in the social sciences involve analyzing binary variables. For example, Best (2009) uses logistic regression to study farmers'decisions whether to adopt organic farming, and Cornwell and Laumann (2011) study sexual dysfunction. Other topics studied with logistic regression include educational attainment (e.g. university degrees) and unemployment.

A dichotomous variable can take two distinct values. As in most regression-based methods, it is convenient to code the variable as a binary variable with the values 0 and 1. Let us assume a variable should indicate whether a person has xenophobic attitudes or not. In this case it would make sense to code xenophobic persons with ‘1’ and non-xenophobic persons with ‘0'.1 How can we analyze this variable?

The Linear Probability Model

One rather ...

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