Analysis Techniques for non-Experimental Data: An Introduction

This book starts with a short refresher course of regression analysis, the workhorse of quantitative analysis. The book next discusses five analysis techniques that make it possible to make causal inference - with the necessary caution: - namely propensity score matching, instrumental variables, the regression discontinuity design, fixed effects models and trajectory analysis. The five analysis techniques are discussed relatively briefly and conceptually, with a minimum of formulas - reason this book cannot be regarded as more than an introduction to each of these techniques. At the end of each chapter there is a list with key publications for each technique that the reader can refer to for more information on statistical issues, and for variations on and special cases of the techniques.