Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-25T06:21:24.396Z Has data issue: false hasContentIssue false
  • English
  • Français

Improving Data Quality in Face-to-Face Survey Research

Published online by Cambridge University Press:  02 October 2019

Carolyn Logan ,
Pablo Parás ,
Michael Robbins Open the ORCID record for Michael Robbins [Opens in a new window]  and
Elizabeth J. Zechmeister Open the ORCID record for Elizabeth J. Zechmeister [Opens in a new window]
Carolyn Logan
Affiliation:
Michigan State University
Pablo Parás
Affiliation:
Data OPM
Michael Robbins
Affiliation:
Princeton University
Elizabeth J. Zechmeister
Affiliation:
Vanderbilt University
Get access Rights & Permissions [Opens in a new window]

Abstract

Data quality in survey research remains a paramount concern for those studying mass political behavior. Because surveys are conducted in increasingly diverse contexts around the world, ensuring that best practices are followed becomes ever more important to the field of political science. Bringing together insights from surveys conducted in more than 80 countries worldwide, this article highlights common challenges faced in survey research and outlines steps that researchers can take to improve the quality of survey data. Importantly, the article demonstrates that with the investment of the necessary time and resources, it is possible to carry out high-quality survey research even in challenging environments in which survey research is not well established.

Type
Article
Information
PS: Political Science & Politics , Volume 53 , Issue 1 , January 2020 , pp. 46 - 50
Copyright
Copyright © American Political Science Association 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

This is an updated version of the original article. For details please see the notice at https://doi.org/10.1017/S1049096519001689

References

REFERENCES

Blasius, Jörg, and Thiessen, Victor. 2015. “Should We Trust Survey Data? Assessing Response Simplification and Data Fabrication.” Social Science Research 52:479–93.CrossRefGoogle ScholarPubMed
Bredl, Sebastian, Winker, Peter, and Kötschau, Kerstin. 2012. “A Statistical Approach to Detect Interviewer Falsification of Survey Data.” Survey Methodology 38 (1): 1–10.Google Scholar
Cohen, Mollie J., and Larrea, Sebastian. 2018. “Assessing and Improving Interview Quality in the 2016/2017 AmericasBarometer.” Methodological Note #002. Nashville, TN: LAPOP. Available at www.vanderbilt.edu/lapop/insights/IMN002en.pdf.Google Scholar
Kuriakose, Noble, and Robbins, Michael. 2016. “Don’t Get Duped: Fraud through Duplication in Public Opinion Surveys.” Statistical Journal of the IAOS 32:283–91.CrossRefGoogle Scholar
Montalvo, J. Daniel, Seligson, Mitchell A., and Zechmeister, Elizabeth J.. 2018. “Improving Adherence to Area Probability Sample Designs: Using LAPOP’s Remote Interview Geo-Locating of Households in Real-Time (RIGHT) System.” Methodological Note #004. Nashville, TN: LAPOP. Available at www.vanderbilt.edu/lapop/insights/IMN004en.pdf.Google Scholar
Spagat, Michael. 2016. “Censorship and Self-Censorship in Research on the Iraq War.” Paper presented at the 57th Annual Convention of the International Studies Association. Atlanta, March 16.Google Scholar