QCA is of questionable value for policy research

Tanner, Sean

doi:10.1016/j.polsoc.2014.08.003

Cited by 14 publications

(10 citation statements)

References 29 publications

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“…Thus for instance, in answer to critiques that the method does not have a strategy for causal identification (Tanner 2014), one could in principle try to declare designs in which instrumental variables strategies, say, are used in combination with QCA estimands.…”

Section: Causal Inferencementioning

confidence: 99%

Declaring and Diagnosing Research Designs

Blair¹,

Cooper²,

Coppock³

et al. 2018

Preprint

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Researchers need to select high-quality research designs and communicate those designs clearly to readers. Both tasks are difficult. We provide a framework for formally "declaring" the analytically relevant features of a research design in a demonstrably complete manner, with applications to qualitative, quantitative, and mixed methods research. The approach to design declaration we describe requires defining a model of the world (M), an inquiry (I), a data strategy (D), and an answer strategy (A). Declaration of these features in code provides sufficient information for researchers and readers to use Monte Carlo techniques to diagnose properties such as power, bias, accuracy of qualitative causal inferences, and other "diagnosands." Ex ante declarations can be used to improve designs and facilitate preregistration, analysis, and reconciliation of intended and actual analyses. Ex post declarations are useful for describing, sharing, reanalyzing, and critiquing existing designs. We provide open-source software, DeclareDesign, to implement the proposed approach.

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Section: Causal Inferencementioning

confidence: 99%

Declaring and Diagnosing Research Designs

Blair¹,

Cooper²,

Coppock³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…QCA has been increasingly used in public health research, although the utility of the method for producing policy-relevant findings has been questioned [29]. The use of QCA in public health research therefore warrants further attention.…”

Section: Discussionmentioning

confidence: 99%

Protocol for a systematic review of the use of qualitative comparative analysis for evaluative questions in public health research

et al. 2019

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BackgroundThere is an increasing recognition that health intervention research requires methods and approaches that can engage with the complexity of systems, interventions, and the relations between systems and interventions. One approach which shows promise to this end is qualitative comparative analysis (QCA), which examines casual complexity across a medium to large number of cases (between 10 and 60+), whilst also being able to generalise across those cases. Increasingly, QCA is being adopted in public health intervention research. However, there is a limited understanding of how it is being adopted. This systematic review will address this gap, examining how it is being used to understand complex causation; for what settings, populations and interventions; and with which datasets to describe cases.MethodsWe will include published and peer-reviewed studies of any public health intervention where the effects on population health, health equity, or intervention uptake are being evaluated. Electronic searches of PubMed, Scopus, Web of Science (incorporating Social Sciences Citation Index and Arts & Humanities Citation Index), Microsoft Academic, and Google Scholar will be performed. This will be supplemented with reference citation tracking and personal contact with experts to identify any additional published studies. Search results will be single screened, with machine learning used to check these results, acting as a ‘second screener’. Any disagreement will be resolved through discussion. Data will be extracted from full texts of eligible studies, which will be assessed against inclusion criteria, and synthesised narratively, using thematic synthesis methods.DiscussionThis systematic review will provide an important map of the increasing use of QCA in public health intervention literature. This review will identify the current scope of research in this area, as well as assessing claims about the utility of the method for addressing complex causation in public health research. We will identify implications for better reporting of QCA methods in public health research and for reporting of case studies such that they can be used in future QCA studies.Systematic review registrationPROSPERO, CRD42019131910

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“…Rather than seeing them as rival research paradigms, scholars interested in QCA estimands can combine the machinery developed in the QCA literature to characterize configurations of conditions with the machinery developed in the broader statistical literature to uncover data generating processes. Thus, for instance, in answer to critiques that the method does not have a strategy for causal identification (Tanner 2014), one could in principle try to declare designs in which instrumental variables strategies, say, are used in combination with QCA estimands.…”

Section: Declaring and Diagnosing Research Designs In Practicementioning

confidence: 99%

Declaring and Diagnosing Research Designs

et al. 2019

View full text Add to dashboard Cite

Researchers need to select high-quality research designs and communicate those designs clearly to readers. Both tasks are difficult. We provide a framework for formally “declaring” the analytically relevant features of a research design in a demonstrably complete manner, with applications to qualitative, quantitative, and mixed methods research. The approach to design declaration we describe requires defining a model of the world (M), an inquiry (I), a data strategy (D), and an answer strategy (A). Declaration of these features in code provides sufficient information for researchers and readers to use Monte Carlo techniques to diagnose properties such as power, bias, accuracy of qualitative causal inferences, and other “diagnosands.” Ex ante declarations can be used to improve designs and facilitate preregistration, analysis, and reconciliation of intended and actual analyses. Ex post declarations are useful for describing, sharing, reanalyzing, and critiquing existing designs. We provide open-source software, DeclareDesign, to implement the proposed approach.

show abstract

QCA is of questionable value for policy research

Cited by 14 publications

References 29 publications

Declaring and Diagnosing Research Designs

Declaring and Diagnosing Research Designs

Protocol for a systematic review of the use of qualitative comparative analysis for evaluative questions in public health research

Declaring and Diagnosing Research Designs

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