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dc.contributor.authorMcMann, Kelly
dc.contributor.authorPemstein, Daniel
dc.contributor.authorSeim, Brigitte
dc.contributor.authorTeorell, Jan
dc.contributor.authorLindberg, Staffan I.
dc.date.accessioned2016-02-04T06:56:53Z
dc.date.available2016-02-04T06:56:53Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/2077/41776
dc.description.abstractSocial scientists face the challenge of determining whether their data are valid, yet they lack prac- tical guidance about how to do so. Existing publications on data validation provide mostly abstract information for creating one’s own dataset or establishing that an existing one is adequate. Fur- ther, they tend to pit validation techniques against each other, rather than explain how to combine multiple approaches. By contrast, this paper provides a practical guide to data validation in which tools are used in a complementary fashion to identify the strengths and weaknesses of a dataset and thus reveal how it can most effectively be used. We advocate for three approaches, each incorporat- ing multiple tools: 1) assessing content validity through an examination of the resonance, domain, differentiation, fecundity, and consistency of the measure; 2) evaluating data generation validity through an investigation of dataset management structure, data sources, coding procedures, aggre- gation methods, and geographic and temporal coverage; and 3) assessing convergent validity using case studies and empirical comparisons among coders and among measures. We apply our method to corruption measures from a new dataset, Varieties of Democracy. We show that the data are generally valid and we emphasize that a particular strength of the dataset is its capacity for analysis across countries and over time. These corruption measures represent a significant contribution to the field because, although research questions have focused on geographic differences and temporal trends, other corruption datasets have not been designed for this type of analysis.sv
dc.description.sponsorshipThe authors are grateful to Nancy Bermeo, Ellen Lust, Gerardo Munck, Andreas Schedler and V-Dem colleagues for their comments on an earlier version of this paper and to Talib Jabbar and Andrew Slivka for their research assistance. This research project was supported by Riksbankens Jubileumsfond, grant M13-0559:1, PI: Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden; by the Knut & Alice Wallenberg Foundation to Wallenberg Academy Fellow Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden; by the Swedish Research Council, PI: Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden & Jan Teorell, Department of Political Science, Lund University, Sweden; and by the National Science Foundation under Grant No. SES-1423944, PI: Daniel Pemstein. Jan Teorell also wishes to acknowledge support from the Wenner-Gren Foundation. We performed simulations and other computational tasks using resources provided by the Notre Dame Center for Research Computing (CRC) through the High Performance Computing section, and by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre in Sweden. We specifically acknowledge the assistance of In-Saeng Suh at CRC and Johan Raber at SNIC in facilitating our use of their respective systems.sv
dc.language.isoengsv
dc.relation.ispartofseriesWorking Paperssv
dc.relation.ispartofseries2016:23sv
dc.titleStrategies of Validation: Assessing the Varieties of Democracy Corruption Datasv
dc.typeTextsv
dc.contributor.organizationV-Dem Institutesv


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