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Research Design in the Social Sciences

Declaration, Diagnosis, and Redesign

Alexander Coppock, Macartan Humphreys, Graeme Blair

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Princeton University Press img Link Publisher

Geisteswissenschaften, Kunst, Musik / Pädagogik

Beschreibung

A state-of-the-art approach to evaluating research design for students and scholars across the social sciences

Assessing the properties of research designs before implementing them can be tricky for even the most seasoned researchers. This book provides a powerful framework—Model, Inquiry, Data Strategy, and Answer Strategy, or MIDA—for describing any empirical research design in the social sciences. MIDA enables you to characterize the key analytic features of observational and experimental designs, qualitative and quantitative designs, and descriptive and causal designs. An accompanying algorithm lets you declare designs in the MIDA framework, diagnose properties such as bias and precision, and redesign features like sampling, assignment, measurement, and estimation procedures. Research Design in the Social Sciences is an essential tool kit for the entire life of a research project, from planning and realization of design to the integration of your results into the scientific literature.

  • A must-have resource for current and future researchers who want to learn about the properties of their designs before they implement them
  • Includes a library of the most common designs in the social sciences
  • Provides a complete declaration of the canonical design for each library entry, describes the circumstances under which the design can be strong or weak, and explores the consequences of the choices under the research designer’s control
  • Accompanied by online resources that can be used in conjunction with the book
  • An ideal textbook for graduate students and advanced undergraduates

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Schlagwörter

DeclareDesign, Observational study, Credibility revolution, Research design, Transparency revolution, Random sampling, Simulation, Randomized controlled trial, Directed acyclic graphs, Experimental study, Power analysis, Quantitative research, Qualitative research