- Geo-Nested Analysis: Mixed-Methods Research with Spatially Dependent Data
- Political Analysis
- Volume | Issue number
- 25 | 3
- Pages (from-to)
- Document type
- Faculty of Social and Behavioural Sciences (FMG)
- Amsterdam Institute for Social Science Research (AISSR)
Mixed-methods designs, especially those where cases selected for small-N analysis (SNA) are nested within a large-N analysis (LNA), have become increasingly popular. Yet, since the LNA in this approach assumes that units are independently distributed, such designs are unable to account for spatial dependence, and dependence becomes a threat to inference, rather than an issue for empirical or theoretical investigation. This is unfortunate, since research in political science has recently drawn attention to diffusion and interconnectedness more broadly. In this paper we develop a framework for mixed-methods research with spatially dependent data—a framework we label “geo-nested analysis”—where insights gleaned at each step of the research process set the agenda for the next phase and where case selection for SNA is based on diagnostics of a spatial-econometric analysis. We illustrate our framework using data from a seminal study of homicides in the United States.
- go to publisher's site
- This article is part of: Marie Curie Fellowship, STATE CAPACITY, Grant #656361
European Union (EU) & Horizon 2020, Euratom & Euratom research & training programme 2014-2018
- Supplementary materials
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