'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.'

Introduction - Christof Wolf and Henning BestPART I: ESTIMATION AND INFERENCEEstimation Techniques: Ordinary least squares and maximum likelihood - Martin ElffBayesian Estimation of Regression Models - Susumu ShikanoPART II: REGRESSION ANALYSIS FOR CROSS-SECTIONSLinear Regression - Christof Wolf and Henning BestRegression Analysis: Assumptions and Diagnostics - Bart Meuleman, Geert Loosveldt and Viktor EmondsNon-Linear and Non-Additive Effects in Linear Regression - Henning LohmannThe Multilevel Regression Model - Joop Hox and Leoniek Wijngaards-de MeijLogistic Regression - Henning Best and Christof WolfRegression Models for Nominal and Ordinal Outcomes - J. Scott LongGraphical Display of Regression Results - Gerrit BauerRegression With Complex Samples - Steven G. Heeringa, Brady T. West and Patricia A. BerglundPART III: CAUSAL INFERENCE AND ANALYSIS OF LONGITUDINAL DATAMatching Estimators for Treatment Effects - Markus GanglInstrumental Variables Regression - Christopher Muller, Christopher Winship and Stephen L. MorganRegression Discontinuity Designs in Social Sciences - David S. Lee and Thomas LemieuxFixed-effects Panel Regression - Josef Bruderl and Volker LudwigEvent History Analysis - Hans-Peter Blossfeld and Gwendoline J. BlossfeldTime-Series Cross-Section - Jessica Fortin-Rittberger