The SAGE Handbook of Regression Analysis and Causal Inference
Henning Best, Christof Wolf · 2014
Introduction - Christof Wolf and Henning Best PART I: ESTIMATION AND INFERENCE Estimation Techniques: Ordinary least squares and maximum likelihood - Martin Elff Bayesian Estimation of Regression Models - Susumu Shikano PART II: REGRESSION ANALYSIS FOR CROSS-SECTIONS Linear Regression - Christof Wolf and Henning Best Regression Analysis: Assumptions and Diagnostics - Bart Meuleman, Geert Loosveldt and Viktor Emonds Non-Linear and Non-Additive Effects in Linear Regression - Henning Lohmann The Multilevel Regression Model - Joop Hox and Leoniek Wijngaards-de Meij Logistic Regression - Henning Best and Christof Wolf Regression Models for Nominal and Ordinal Outcomes - J. Scott Long Graphical Display of Regression Results - Gerrit Bauer Regression With Complex Samples - Steven G. Heeringa, Brady T. West and Patricia A. Berglund PART III: CAUSAL INFERENCE AND ANALYSIS OF LONGITUDINAL DATA Matching Estimators for Treatment Effects - Markus Gangl Instrumental Variables Regression - Christopher Muller, Christopher Winship and Stephen L. Morgan Regression Discontinuity Designs in Social Sciences - David S. Lee and Thomas Lemieux Fixed-effects Panel Regression - Josef Bruderl and Volker Ludwig Event History Analysis - Hans-Peter Blossfeld and Gwendoline J. Blossfeld Time-Series Cross-Section - Jessica Fortin-Rittberger