- 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 ...
Chapter 4: Linear Regression
In this chapter we first present the basic idea of linear regression and give a non-technical introduction. Next we cover the statistical basis of this method and discuss estimation, testing and interpretation of regression results. The third section is devoted to the presentation of an example analysis. In closing, we first discuss issues related to the causal interpretation of OLS regression coefficients and then mention some general problems encountered in linear regression and recommend further reading.
In science we often are interested in studying hypotheses of the form ‘the more X, the more/less Y’, for example ‘the higher the education of a person is, the more willing s/he is to accept immigrants’. Thus, we assume that acceptance of immigrants is partly ...