• 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 ...

Regression Discontinuity Designs in Social Sciences
Regression discontinuity designs in social sciences
David S.Lee and ThomasLemieux*
Introduction

Regression discontinuity (RD) designs were initially introduced by Thistlethwaite and Campbell (1960) as a way of estimating treatment effects in a non-experimental setting where treatment is determined by whether an observed ‘assignment' variable (also referred to in the literature as the ‘forcing' variable or the ‘running' variable) exceeds a known cutoff point. Thistlethwaite and Campbell (1960) analyzed the impact of merit awards on future academic outcomes in their original study, using the fact that the allocation of these awards was based on an observed test score. The main idea behind the research design was that individuals with scores just below the cutoff (who did not receive the award) were good comparisons ...

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