Description
Sage Publications Ltd The SAGE Handbook of Regression Analysis and Causal Inference 2014 Edition by Henning Best, Christof Wolf
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 both cross-sectional and panel data analysis.'-Tom Smith, Senior Fellow, NORC, University of ChicagoEdited and written by a team of leading international social scientists, this Handbook provides a comprehensive introduction to multivariate methods. The Handbook focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities.Each Part starts with a non-mathematical introduction to the method covered in that section, giving readers a basic knowledge of the method's logic, scope and unique features. Next, the mathematical and statistical basis of each method is presented along with advanced aspects. Using real-world data from the European Social Survey (ESS) and the Socio-Economic Panel (GSOEP), the book provides a comprehensive discussion of each method's application, making this an ideal text for PhD students and researchers embarking on their own data analysis. Table of contents :- 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