Handbook of Causal Analysis for Social Research (Handbooks of Sociology and Social Research) 🔍
Stephen L. Morgan (auth.), Stephen L. Morgan (eds.) Springer Netherlands, Handbooks of Sociology and Social Research, Handbooks of Sociology and Social Research, 1, 2013
英语 [en] · PDF · 4.9MB · 2013 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save
描述
What constitutes a causal explanation, and must an explanation be causal? What warrants a causal inference, as opposed to a descriptive regularity? What techniques are available to detect when causal effects are present, and when can these techniques be used to identify the relative importance of these effects? What complications do the interactions of individuals create for these techniques? When can mixed methods of analysis be used to deepen causal accounts? Must causal claims include generative mechanisms, and how effective are empirical methods designed to discover them? The __Handbook of Causal Analysis for Social Research__ tackles these questions with nineteen chapters from leading scholars in sociology, statistics, public health, computer science, and human development.
备用文件名
lgrsnf/A:\compressed\10.1007%2F978-94-007-6094-3.pdf
备用文件名
nexusstc/Handbook of Causal Analysis for Social Research/d8312841e0abcf202cc9e5da4104edbb.pdf
备用文件名
scihub/10.1007/978-94-007-6094-3.pdf
备用文件名
zlib/Mathematics/Stephen L. Morgan (auth.), Stephen L. Morgan (eds.)/Handbook of Causal Analysis for Social Research_2136194.pdf
备选作者
Morgan (Ed.), Stephen L.
备用出版商
Springer Science + Business Media BV
备用出版商
Springer London, Limited
备用版本
Handbooks of sociology and social research, Dordrecht, ©2013
备用版本
Handbooks of Sociology and Social Research, uuuu
备用版本
Springer Nature, Dordrecht, 2013
备用版本
Netherlands, Netherlands
备用版本
2013, PS, 2013
备用版本
May 04, 2013
元数据中的注释
sm23112031
元数据中的注释
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元数据中的注释
Source title: Handbook of Causal Analysis for Social Research (Handbooks of Sociology and Social Research)
备用描述
What Constitutes A Causal Explanation, And Must An Explanation Be Causal? What Warrants A Causal Inference, As Opposed To A Descriptive Regularity? What Techniques Are Available To Detect When Causal Effects Are Present, And When Can These Techniques Be Used To Identify The Relative Importance Of These Effects? What Complications Do The Interactions Of Individuals Create For These Techniques? When Can Mixed Methods Of Analysis Be Used To Deepen Causal Accounts? Must Causal Claims Include Generative Mechanisms, And How Effective Are Empirical Methods Designed To Discover Them? The Handbook Of Causal Anlaysis For Social Research Tackles These Questions With Nineteen Chapters From Leading Scholars In Sociology, Statistics, Public Health, Computer Science, And Human Development. Background And Approaches To Analysis -- A History Of Causal Analysis In The Social Sciences / Sondra N. Barringer, Scott R. Eliason, Erin Leahey -- Types Of Causes / Jeremy Freese, J. Alex Kevern -- Design And Modeling Choices. Research Design: Toward A Realistic Role For Causal Analysis / Herbert L. Smith -- Causal Models And Counterfactuals / James Mahoney, Gary Goertz, Charles C. Ragin -- Mixed Methods And Causal Analysis / David J. Harding, Kristin S. Seefeldt -- Beyond Conventional Regression Models. Fixed Effects, Random Effects, And Hybrid Models For Causal Analysis / Glenn Firebaugh, Cody Warner, Michael Massoglia -- Heteroscedastic Regression Models For The Systematic Analysis Of Residual Variances / Hui Zheng, Yang Yang, Kenneth C. Land -- Group Differences In Generalized Linear Models / Tim F. Liao -- Counterfactual Causal Analysis And Nonlinear Probability Models / Richard Breen, Kristian Bernt Karlson -- Causal Effect Heterogeneity / Jennie E. Brand, Juli Simon Thomas -- New Perspectives On Causal Mediation Analysis / Xiaolu Wang, Michael E. Sobel -- Systems Of Causal Relationships. Graphical Causal Models / Felix Elwert -- The Causal Implications Of Mechanistic Thinking: Identification Using Directed Acyclic Graphs (dags) / Carly R. Knight, Christopher Winship -- Eight Myths About Causality And Structural Equation Models / Kenneth A. Bollen, Judea Pearl -- Influence And Interference. Heterogeneous Agents, Social Interactions, And Causal Inference / Guanglei Hong, Stephen W. Raudenbush -- Social Networks And Causal Inference / Tyler J. Vanderweele, Weihua An -- Retreat From Effect Identification. Partial Identification And Sensitivity Analysis / Markus Gangl -- What You Can Learn From Wrong Causal Models / Richard A. Berk ... [et Al.] Stephen L. Morgan (ed.). Includes Bibliographical References.
备用描述
Front Matter....Pages i-xi
Introduction....Pages 1-5
Front Matter....Pages 7-7
A History of Causal Analysis in the Social Sciences....Pages 9-26
Types of Causes....Pages 27-41
Front Matter....Pages 43-43
Research Design: Toward a Realistic Role for Causal Analysis....Pages 45-73
Causal Models and Counterfactuals....Pages 75-90
Mixed Methods and Causal Analysis....Pages 91-110
Front Matter....Pages 111-111
Fixed Effects, Random Effects, and Hybrid Models for Causal Analysis....Pages 113-132
Heteroscedastic Regression Models for the Systematic Analysis of Residual Variances....Pages 133-152
Group Differences in Generalized Linear Models....Pages 153-166
Counterfactual Causal Analysis and Nonlinear Probability Models....Pages 167-187
Causal Effect Heterogeneity....Pages 189-213
New Perspectives on Causal Mediation Analysis....Pages 215-242
Front Matter....Pages 243-243
Graphical Causal Models....Pages 245-273
The Causal Implications of Mechanistic Thinking: Identification Using Directed Acyclic Graphs (DAGs)....Pages 275-299
Eight Myths About Causality and Structural Equation Models....Pages 301-328
Front Matter....Pages 329-329
Heterogeneous Agents, Social Interactions, and Causal Inference....Pages 331-352
Social Networks and Causal Inference....Pages 353-374
Front Matter....Pages 375-375
Partial Identification and Sensitivity Analysis....Pages 377-402
What You Can Learn from Wrong Causal Models....Pages 403-424
备用描述
What constitutes a causal explanation, and must an explanation be causal? What warrants a causal inference, as opposed to a descriptive regularity? What techniques are available to detect when causal effects are present, and when can these techniques be used to identify the relative importance of these effects? What complications do the interactions of individuals create for these techniques? When can mixed methods of analysis be used to deepen causal accounts? Must causal claims include generative mechanisms, and how effective are empirical methods designed to discover them? This book tackles these questions with nineteen chapters from leading scholars in sociology, statistics, public health, computer science, and human development
备用描述
Handbooks of Sociology and Social Research
Erscheinungsdatum: 04.05.2013
开源日期
2013-08-01
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