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Mixing Methods in the Discipline of Politics

This article discusses the use of quantitative and qualitative methods in political research. It explores the strengths and weaknesses of each approach and proposes Lieberman's framework for mixing methods. The framework involves using large-N quantitative analyses and small-N qualitative analyses to test and build models. Several examples of studies using this framework are provided.

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Mixing Methods in the Discipline of Politics

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  1. Mixing Methodsin the Discipline of Politicsby Renske Doorenspleet

  2. (A) Quantitative and Qualitative Methods Qualitative methods: • Words • Small-N • Cases central • Points of view of participants • Researcher close • Theory development • Process • Unstructured • Contextual understanding • Rich, deep data • Micro Quantitative methods: • Numbers • Large-N • Variables central • Point of view of researcher • Researcher distant • Theory testing • Static • Structured • Generalization • Hard, reliable data • Macro see also Bryman(2004: pp.286-288)

  3. (B) Mixing Methods: Lieberman’s framework • How would you investigate the same questions by using mixed methods? • Tarrow (1995): triangulation: use of qualitative and quantitative methods to answer one and the same research question • But how? Read: Lieberman, E.S. (2005). ‘Nested Analysis as a Mixed-Method Strategy for Comparative Research’ in American Political Science Review, vol.99, no. 13, pp. 435-452

  4. (B) Mixing Methods: Lieberman’s framework • Explanation framework Two crucial steps: • large-N quantitative analyses (LNA) • small-N qualitative analyses (SNA) • model testing • model building

  5. (B) Mixing Methods: Lieberman’s framework • Some examples of studies using framework • Relationship economic development and democracy • Relationship civic culture and welfare • Relationship international trade and human rights

  6. (C) Mixing Methods: Strengths and Weaknesses • Strengths: combination of best of both worlds • Better concepts and measurements; caused by more internal validity (SNA) and more external validity (LNA) • Better case selection; clear guidelines and criteria for case selection in SNA • Better contribution to theory development

  7. (C) Mixing Methods: Strengths and Weaknesses • Weaknesses 1. Not always better concepts and measurements 2. SNA is nested within LNA, so in the end LNA determines research agenda 3. Incompatibility thesis

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