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Qualitative Comparative Analysis with R A Users Guide [Paperback]

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  • Category: Books (Political Science)
  • Author:  Thiem, Alrik, Dusa, Adrian
  • Author:  Thiem, Alrik, Dusa, Adrian
  • ISBN-10:  1461445833
  • ISBN-10:  1461445833
  • ISBN-13:  9781461445838
  • ISBN-13:  9781461445838
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  125
  • Pages:  125
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Mar-2012
  • Pub Date:  01-Mar-2012
  • SKU:  1461445833-11-SPRI
  • SKU:  1461445833-11-SPRI
  • Item ID: 100247045
  • List Price: $69.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Jul 04 to Jul 06
  • Notes: Brand New Book. Order Now.

Social science theory often builds on sets and their relations. Correlation-based methods of scientific enquiry, however, use linear algebra and are unsuited to analyzing set relations. The development of Qualitative Comparative Analysis (QCA) by Charles Ragin has given social scientists a formal tool for identifying set-theoretic connections based on Boolean algebra. As a result, interest in this method has markedly risen among social scientists in recent years. This book offers the first complete introduction on how to perform QCA in the R software environment for statistical computing and graphics with the QCA package. Developed as a comprehensive solution, QCA provides an unprecedented scope of functionality for analyzing crisp, multi-value and fuzzy sets. The reader is not required to have knowledge of R, but the book assumes an understanding of the fundamentals of QCA. Using examples from published work, the authors demonstrate how to make the most of QCAs wide-ranging capabilities for the readers own purposes. Although mainly written for political scientists, this book is also of interest to scholars from other disciplines in the social sciences such as sociology, business, management, organization, anthropology, education and health.

1.Loading Neccessary Packages.- 2. Reading Data into R.- 3. Testing for Neccessity.- 4. Testing for Sufficiency 5.- Sufficiency: Parameters of Fit 6.- Plotting Results

Offers first complete introduction on how to conduct QCA in the R software environment for statistical computing and graphics

Using the QCA package, illustrates how to perform csQCA, mvQCA and fsQCA, including the graphical visualization of results

Introduces new theoretical concepts and procedures, including parameters of fit and intermediate solutions for mvQCA

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