Handbook of Causal Analysis for Social Research [Paperback]

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.??

Preface.- Chapter 1. Introduction; Stephen L. Morgan.- PART I. BACKGROUND AND APPROACHES TO ANALYSIS.- Chapter?2. A History of Causal Analysis in the Social Sciences; Sondra N. Barringer, Erin Leahey and Scott R. Eliason.- Chapter 3. Types of Causes; Jeremy Freese and J. Alex Kevern.- PART II. DESIGN AND MODELING CHOICES.- Chapter 4. Research Design:?Toward a Realistic Role for Causal Analysis;?Herbert L.?Smith.- Chapter?5. Causal Models and Counterfactuals; James Mahoney, Gary Goertz and Charles C. Ragin.- Chapter 6. Mixed Models and Counterfactuals; David J. Harding and Kristin S. Seefeldt.- PART III. BEYOND CONVENTIONAL REGRESSION MODELS.- Chapter 7.?Fixed Effects, Random Effects, and Hybrid Models for Causal Analysis; Glenn?Firebaugh, Cody Warner, and Michael Massoglia.- Chapter 8. Heteroscedastic Regression Models for the Systematic Analysis of Residual Variance; Hui Zheng, Yang Yang and Kennl£