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Assessing Data Quality: An Approach and An Application

Published online by Cambridge University Press:  15 September 2021

Kelly McMann
Affiliation:
Political Science, Case Western Reserve University, Cleveland, OH44106, USA. Email: kelly.mcmann@case.edu
Daniel Pemstein
Affiliation:
Political Science and Public Policy & Challey Institute, North Dakota State University, Fargo, ND58102, USA. Email: daniel.pemstein@ndsu.edu
Brigitte Seim*
Affiliation:
Public Policy, University of North Carolina, Chapel Hill, NC27599, USA. Email: seimbri@gmail.com
Jan Teorell
Affiliation:
Political Science, Lund University, Lund, 221 00, Sweden. Email: jan.teorell@svet.lu.se
Staffan Lindberg
Affiliation:
V-Dem Institute & Political Science, University of Gothenburg, Gothenburg, 413 27, Sweden. Email: staffan.i.lindberg@pol.gu.se
*
Corresponding author Brigitte Seim

Abstract

Political scientists routinely face the challenge of assessing the quality (validity and reliability) of measures in order to use them in substantive research. While stand-alone assessment tools exist, researchers rarely combine them comprehensively. Further, while a large literature informs data producers, data consumers lack guidance on how to assess existing measures for use in substantive research. We delineate a three-component practical approach to data quality assessment that integrates complementary multimethod tools to assess: (1) content validity; (2) the validity and reliability of the data generation process; and (3) convergent validity. We apply our quality assessment approach to the corruption measures from the Varieties of Democracy (V-Dem) project, both illustrating our rubric and unearthing several quality advantages and disadvantages of the V-Dem measures, compared to other existing measures of corruption.

Type
Article
Copyright
© The Author(s) 2021. Published by Cambridge University Press on behalf of the Society for Political Methodology

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Footnotes

Edited by Jeff Gill

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