The Sage handbook of regression analysis and causal inference
The Sage handbook of regression analysis and causal inference
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Sage 回归分析和因果推理手册
DOI:
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发表时间:
2014
期刊:
影响因子:
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通讯作者:
C. Wolf
中科院分区:
文献类型:
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作者:
H. Best;C. Wolf
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