Transforming Quantitative Datasets Using Principles of Research Design: Finding a Way to Distinguish Between Domestic and Transnational Terror Attacks

Abstract

In some cases, existing datasets can be used to generate measures of distinct concepts for which data are otherwise unavailable. There are different ways to dissect, transform, and rebuild datasets, and with some creativity, datasets can be transformed to fill critical holes or provide new information on a variety of phenomena. However, good practices are required to generate a useful end product. We used data on terror attacks to address the lack of information on the origin of terror groups, which was otherwise unavailable and therefore limited the types of questions that could be assessed. Our new measure of terror groups’ “home country” was designed to fill this gap. This case study overviews the process that we used to develop our measure. First, we clearly conceptualized our term of a “home country,” which is critical as the concept serves as the foundation for the data project. Second, we operationalized that concept, paying attention to measurement validity, reliability, and replicability to generate a valuable measure that is rooted in the principles of research design. This case study discusses the importance of these steps—careful conceptualization and operationalization—as the keys to successfully generate a new measure from existing data sources.

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