Spatial Heterogeneity and Mixed-Methods Research

• In Event: Measurement and Method

Abstract

This paper explores how mixed-methods research, quantitative spatial analysis, and qualitative field research can benefit from a greater dialogue between large-N and small-N analyses that incorporates spatial methods in mixed-methods research. The particular focus of this paper is on spatial approaches for modeling spatial non-stationarity in parameters: varying effects of the covariates in a model across the spatial plane. Multiple large-N quantitative spatial approaches have been developed to identify and model such spatial heterogeneity. These quantitative approaches can provide new insights for qualitative scholars by pointing toward spatially varying causal relationships across the cases they know better than most large-N quantitative scholars. The in-depth field research that is subsequently pursued by qualitative researchers can provide causal explanations for the spatially varying relationships and avoid the post-hoc interpretation of spatially varying parameters that is common to many applications of spatial non-stationarity modeling approaches.

Author

• David Darmofal, University of South Carolina