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Handbook of causal analysis for social research / edited by Stephen L. Morgan

Contributor(s): Material type: TextTextSeries: Handbooks of sociolgy and social researchPublisher: Dordrecht : Springer, 2013Description: xi, 424 p. : ill. ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 978-9401794077
Subject(s): DDC classification:
  • 300 23
Available additional physical forms:
  • Also issued online.
Summary: This book reviews the tremendous progress of the past 15 years in the causal analysis of non-experimental data, also known as observational data, and shows how to use state-of-the-art methods for causal analysis in basic and applied empirical scholarship.Summary: 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.
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Holdings
Item type Current library Call number Status Date due Barcode
REGULAR University of Wollongong in Dubai PHD Shelf 300.72 HA ND (Browse shelf(Opens below)) Available T0050836

Includes bibliographical references.

Also issued online.

This book reviews the tremendous progress of the past 15 years in the causal analysis of non-experimental data, also known as observational data, and shows how to use state-of-the-art methods for causal analysis in basic and applied empirical scholarship.

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.

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