Next Article in Journal
Development of the Non-Iterative Supervised Learning Predictor Based on the Ito Decomposition and SGTM Neural-Like Structure for Managing Medical Insurance Costs
Previous Article in Journal
CRC806-KB: A Semantic MediaWiki Based Collaborative Knowledge Base for an Interdisciplinary Research Project
Open AccessArticle

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

1
GESIS—Leibniz Institute for the Social Sciences, Unter Sachsenhausen 6–8, 50667 Cologne, Germany
2
Service Center eSciences, Trier University, 54286 Trier, Germany
*
Author to whom correspondence should be addressed.
Received: 2 October 2018 / Revised: 23 October 2018 / Accepted: 25 October 2018 / Published: 29 October 2018
  |  
PDF [224 KB, uploaded 30 October 2018]

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. View Full-Text
Keywords: total survey error; data quality; documentation quality; methodology reports; data sharing; reproducibility; open science total survey error; data quality; documentation quality; methodology reports; data sharing; reproducibility; open science
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Jedinger, A.; Watteler, O.; Förster, A. Improving the Quality of Survey Data Documentation: A Total Survey Error Perspective. Data 2018, 3, 45.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Data EISSN 2306-5729 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top