Description:

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Meta-analysis is a sophisticated and important tool for the purposes of cumulative knowledge production. However, traditional approaches to meta-analysis systematically exclude qualitative scholarship. In this paper, I propose and develop a systematic framework to incorporate qualitative and quantitative study information into a single meta-analysis; I term this approach to meta-analysis Bayesian Integrative Meta-Analysis. Drawing on existing literature in Bayesian elicitation strategies for constructing informed prior distributions, I show how information from qualitative manuscripts can be systematically converted into a Bayesian prior distribution through a process I call conversion elicitation. The resulting posterior distribution of the Bayesian meta-analysis is therefore a result of a qualitatively informed prior and a likelihood distribution composed of the effect sizes from quantitative studies. I explain the framework for BIMA using a case study with simulated data and an applied example related to the effect of competitive wages on bureaucratic corruption.

Sarah Moore is currently a PhD candidate in Comparative Politics and Master of Science student in Statistics at Northwestern University. Her broad interests include the legacies of political violence, mixed-methods research, and civilian resistance in Latin America. Moore's dissertation is a collection of essays that devise quantitative and qualitative methods for the improved study of difficult-to-research phenomena, with specific applications to the study of organized violence. Informed by her additional training in psychometric theory and sociological qualitative methods, these four essays provide methodological solutions for sampling, measurement of concepts, and inference of preferences where randomization is not possible. Her research is supported by the Buffett Institute for Global Affairs at Northwestern University. She has also served as a Predoctoral Research Fellow with Universidad de los Andes in Bogotá.