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Set-Theoretic Multi-Method Research: A Guide to Combining QCA and Case Studies

Set-Theoretic Multi-Method Research: A Guide to Combining QCA and Case Studies

Set-Theoretic Multi-Method Research: A Guide to Combining QCA and Case Studies Paperback / softback - 2024

by Carsten Q. Schneider

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Paperback / softback. New. A comprehensive introduction to combining Qualitative Comparative Analysis (QCA) and case studies using R software. With its practical focus, this book facilitates the efficient and independent learning of SMMR (set-theoretic multi-method research) for students, researchers, and practitioners in the social sciences.
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Details

  • Title Set-Theoretic Multi-Method Research: A Guide to Combining QCA and Case Studies
  • Author Carsten Q. Schneider
  • Binding Paperback
  • Condition New
  • Pages 276
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press
  • Publication date 2024-02-29
  • Features Bibliography, Glossary, Index
  • Bookseller's Inventory # B9781009307192
  • ISBN 9781009307192 / 1009307193
  • Weight 0.82 lbs (0.37 kg)
  • Dimensions 9 x 6 x 0.58 in (22.86 x 15.24 x 1.47 cm)
  • Category Sociology
  • Library of Congress subjects Set theory, Social sciences - Mathematical models
  • Library of Congress Catalogue Number 2023024831
  • Dewey Decimal Code 300.72
  • Quantity available 10

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From the publisher

A state-of-the-art comprehensive exposition of combining Qualitative Comparative Analysis (QCA) and case studies, this book facilitates the efficient use and independent learning of this form of SMMR (set-theoretic multi-method research) with the best available software. It will reduce the time and effort required when performing both QCA and case studies within the same research project. This is achieved by spelling out the conceptual principles and practices in SMMR, and by introducing a tailor-made R software package. With an applied and practical focus, this is an intuitive resource for implementing the most complete protocol of SMMR. Features include Learning Goals, Core Points, and Empirical Examples, as well as boxed examples of R codes and the R output it produces. There is also a glossary for key SMMR terms. Additional online material is available, comprising machine-readable datasets and R scripts for replication and independent learning.

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