Best / Wolf The SAGE Handbook of Regression Analysis and Causal Inference

1. Auflage 2014
ISBN: 978-1-4739-0835-2
Verlag: SAGE Publications
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 424 Seiten, Format (B × H): 184 mm x 246 mm

'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 Chicago

Edited 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.

Autoren/Hrsg.

Best, Henning

Wolf, Christof

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Forschungsmethodik, Wissenschaftliche Ausstattung

Inhaltsverzeichnis

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