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Now, later, or never? Using response-time patterns to predict panel attrition

[journal article]

Minderop, Isabella
Weiß, Bernd

Abstract

Preventing panel members from attriting is a fundamental challenge for panel surveys. Research has shown that response behavior in earlier waves (response or nonresponse) is a good predictor of panelists' response behavior in upcoming waves. However, response behavior can be described in greater det... view more

Preventing panel members from attriting is a fundamental challenge for panel surveys. Research has shown that response behavior in earlier waves (response or nonresponse) is a good predictor of panelists' response behavior in upcoming waves. However, response behavior can be described in greater detail by considering the time until the response is returned. In the present study, we investigated whether respondents who habitually return their survey late and respondents who switch between early and late response in multiple waves are more likely to attrit from a panel. Using data from the GESIS Panel, we found that later response is related to a higher likelihood of attrition (AME = 0.087) and that response-time stability is related to a lower likelihood of attrition (AME = −0.013). Our models predicted most cases of attrition; thus, survey practitioners could potentially predict future attriters by applying these models to their own data.... view less

Keywords
prognosis; survey; panel; data quality; response behavior; survey research; data capture

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Free Keywords
Reluctant response; panel survey; paradata; late response; ZA5664: GESIS Panel - Extended Edition (Datenfile Version 26.0.0)

Document language
English

Publication Year
2022

Page/Pages
p. 1-14

Journal
International Journal of Social Research Methodology (2022)

DOI
https://doi.org/10.1080/13645579.2022.2091259

ISSN
1464-5300

Status
Published Version; peer reviewed

Licence
Creative Commons - Attribution-Noncommercial-No Derivative Works 4.0

FundingGefördert durch die Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 491156185 / Funded by the German Research Foundation (DFG) - Project number 491156185


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.