Building on Solid Ground: Robust Case Selection in Multi‐Method Research

Rohlfing, Ingo; Starke, Peter

doi:10.1111/spsr.12052

Cited by 10 publications

(4 citation statements)

References 61 publications

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“… 1. See Goerres and Prinzen (2012), Rohlfing (2008), Rohlfing and Starke (2013), and Seawright and Gerring (2008) for method-centered discussions. …”

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confidence: 99%

A Unifying Framework for Causal Analysis in Set-Theoretic Multimethod Research

Rohlfing

Schneider²

2016

Sociological Methods & Research

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The combination of Qualitative Comparative Analysis (QCA) with process tracing, which we call set-theoretic multimethod research (MMR), is steadily becoming more popular in empirical research. Despite the fact that both methods have an elected affinity based on set theory, it is not obvious how a within-case method operating in a single case and a cross-case method operating on a population of cases are compatible and can be combined in empirical research. There is a need to reflect on whether and how set-theoretic MMR is internally coherent and how QCA and process tracing can be integrated in causal analysis. We develop a unifying foundation for causal analysis in set-theoretic MMR that highlights the roles and interplay of QCA and process tracing. We argue that causal inference via counterfactuals on the level of single cases integrates QCA and process tracing and assigns proper and equally valuable roles to both methods.

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“… 1. See Goerres and Prinzen (2012), Rohlfing (2008), Rohlfing and Starke (2013), and Seawright and Gerring (2008) for method-centered discussions. …”

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confidence: 99%

A Unifying Framework for Causal Analysis in Set-Theoretic Multimethod Research

Rohlfing

Schneider²

2016

Sociological Methods & Research

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“…5), the informal logic of case selection on the basis of crisp-set QCA results for necessity and sufficiency (Ragin and Schneider 2011), and the insights that can be derived from QCA in order to sharpen the focus of follow-up case studies, and vice versa Schneider and Rohlfing (Rohlfing and Schneider 2013;Schneider and Rohlfing 2013). This literature makes important contributions to the development of set-theoretic MMR, for the unreflected transfer of principles and practices from the better known regression-based MMR (e.g., Goerres and Prinzen 2012;Lieberman 2005;Rohlfing 2008; Rohlfing and Starke 2013) is not meaningful due to important differences between regression analysis and set theory-based QCA (Goertz and Mahoney 2012: chap. 17;Ragin 2008: chap.…”

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confidence: 99%

Case Studies Nested in Fuzzy-set QCA on Sufficiency

Schneider¹,

Rohlfing

2014

Sociological Methods & Research

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114

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Qualitative Comparative Analysis (QCA) is a method for cross-case analyses that works best when complemented with follow-up case studies focusing on the causal quality of the solution and its constitutive terms, the underlying causal mechanisms, and potentially omitted conditions. The anchorage of QCA in set theory demands criteria for follow-up case studies that are different from those known from regression-based multimethod research (MMR). Based on the evolving research on set-theoretic MMR, we introduce principles for formalized case selection and causal inference after a fuzzy-set QCA on sufficiency. Using an empirical example for illustration, we elaborate on the principles of counterfactuals for intelligible causal inference in the analysis of three different types of cases. Furthermore, we explain how case-based counterfactual inferences on the basis of QCA solutions are related to counterfactuals in the course of processing a truth table in order to produce a solution. We then flesh out two important functions that ideal types play for QCA-based case studies: First, they inform the development of formulas for the choice of the best available cases for with-case analysis and, second, establish the boundaries of generalization of the causal inferences.

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“…9We assume that researchers are mindful of the uncertainty inherent in all models (Rohlfing and Starke 2013) and have diligently tested their models for misspecification (Rohlfing 2008). …”

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Geo-Nested Analysis: Mixed-Methods Research with Spatially Dependent Data

Harbers

Ingram

2017

Polit. Anal.

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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.

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Building on Solid Ground: Robust Case Selection in Multi‐Method Research

Cited by 10 publications

References 61 publications

A Unifying Framework for Causal Analysis in Set-Theoretic Multimethod Research

A Unifying Framework for Causal Analysis in Set-Theoretic Multimethod Research

Case Studies Nested in Fuzzy-set QCA on Sufficiency

Geo-Nested Analysis: Mixed-Methods Research with Spatially Dependent Data

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