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Handbook of Causal Analysis for Social Research

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Cover of 'Handbook of Causal Analysis for Social Research'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 A History of Causal Analysis in the Social Sciences
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    Chapter 3 Types of Causes
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    Chapter 4 Research Design: Toward a Realistic Role for Causal Analysis
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    Chapter 5 Causal Models and Counterfactuals
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    Chapter 6 Mixed Methods and Causal Analysis
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    Chapter 7 Fixed Effects, Random Effects, and Hybrid Models for Causal Analysis
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    Chapter 8 Heteroscedastic Regression Models for the Systematic Analysis of Residual Variances
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    Chapter 9 Group Differences in Generalized Linear Models
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    Chapter 10 Counterfactual Causal Analysis and Nonlinear Probability Models
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    Chapter 11 Causal Effect Heterogeneity
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    Chapter 12 New Perspectives on Causal Mediation Analysis
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    Chapter 13 Graphical Causal Models
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    Chapter 14 The Causal Implications of Mechanistic Thinking: Identification Using Directed Acyclic Graphs (DAGs)
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    Chapter 15 Eight Myths About Causality and Structural Equation Models
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    Chapter 16 Heterogeneous Agents, Social Interactions, and Causal Inference
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    Chapter 17 Social Networks and Causal Inference
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    Chapter 18 Partial Identification and Sensitivity Analysis
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    Chapter 19 What You Can Learn from Wrong Causal Models
Attention for Chapter 14: The Causal Implications of Mechanistic Thinking: Identification Using Directed Acyclic Graphs (DAGs)
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