Improving the Quality of Survey Data Documentation: A Total Survey Error Perspective

Alexander Jedinger, Oliver Watteler and André Förster
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Alexander Jedinger: GESIS—Leibniz Institute for the Social Sciences, Unter Sachsenhausen 6–8, 50667 Cologne, Germany
Oliver Watteler: GESIS—Leibniz Institute for the Social Sciences, Unter Sachsenhausen 6–8, 50667 Cologne, Germany
André Förster: Service Center eSciences, Trier University, 54286 Trier, Germany

Data, 2018, vol. 3, issue 4, 1-10

Abstract: Surveys are a common method in the social and behavioral sciences to collect data on attitudes, personality and social behavior. Methodological reports should provide researchers with a complete and comprehensive overview of the design, collection and statistical processing of the survey data that are to be analyzed. As an important aspect of open science practices, they should enable secondary users to assess the quality and the analytical potential of the data. In the present article, we propose guidelines for the documentation of survey data that are based on the total survey error approach. Considering these guidelines, we conclude that both scientists and data-holding institutions should become more sensitive to the quality of survey data documentation.

Keywords: total survey error; data quality; documentation quality; methodology reports; data sharing; reproducibility; open science (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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