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Assessing Data Quality : An Approach and An Application

McMann, Kelly ; Pemstein, Daniel ; Seim, Brigitte ; Teorell, Jan LU orcid and Lindberg, Staffan LU (2022) In Political Analysis 30(3). p.426-449
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... (More)

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.

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Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Bayesian IRT, corruption, reliability, validity
in
Political Analysis
volume
30
issue
3
pages
426 - 449
publisher
Cambridge University Press
external identifiers
  • scopus:85115156693
ISSN
1047-1987
DOI
10.1017/pan.2021.27
language
English
LU publication?
yes
additional info
Publisher Copyright: © The Author(s) 2021. Published by Cambridge University Press on behalf of the Society for Political Methodology.
id
edb2f56f-14d1-45f6-88fc-5e2c8a47d998
date added to LUP
2021-10-12 15:34:56
date last changed
2022-06-30 00:23:48
@article{edb2f56f-14d1-45f6-88fc-5e2c8a47d998,
  abstract     = {{<p>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.</p>}},
  author       = {{McMann, Kelly and Pemstein, Daniel and Seim, Brigitte and Teorell, Jan and Lindberg, Staffan}},
  issn         = {{1047-1987}},
  keywords     = {{Bayesian IRT; corruption; reliability; validity}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{426--449}},
  publisher    = {{Cambridge University Press}},
  series       = {{Political Analysis}},
  title        = {{Assessing Data Quality : An Approach and An Application}},
  url          = {{http://dx.doi.org/10.1017/pan.2021.27}},
  doi          = {{10.1017/pan.2021.27}},
  volume       = {{30}},
  year         = {{2022}},
}