2019/05/31 by Graeme Blair, Jasper Cooper, Alexander Coppock +1 · 1 voice · 7 citations
Social Sciences · Mathematics · Decision Sciences · #Qualitative Comparative Analysis Research #Advanced Causal Inference Techniques #Evaluation and Performance Assessment
paper · pdf · doi:10.1017/s0003055419000194
openalex publication_date 2019/05/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
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.