What You See and What You Get: Pitfalls and Principles of Nested Analysis in Comparative Research

In a recent contribution to this journal, Munck and Snyder found that many studies suffer from a deficient application of qualitative and quantitative methods. They argue that the combination of small-n and large-n analysis represents a viable method for promoting the production of knowledge. Recently, Evan Lieberman proposed nested analysis as a rigorous approach for comparative research that builds on the complementary strengths of quantitative and qualitative analysis. In this paper, the author examines the methodological potential of nested inference to advance comparative political analysis, arguing that the specific methodological problems of nested designs have not been fully appreciated. It is shown that, under certain circumstances, nothing is gained from a nested analysis. On the contrary, one might lose more than one gains compared to single-method designs. The author suggests specific methodological principles that take these problems into account to make nested analysis fruitful for comparative studies.