The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Selection Bias in Web Surveys
Open accessAbstract
Summary: At first sight, web surveys seem to be an interesting and attractive means of data collection. They provide simple, cheap, and fast access to a large group of potential respondents. However, web surveys are not without methodological problems. Specific groups in the populations are under‐represented because they have less access to Internet. Furthermore, recruitment of respondents is often based on self‐selection. Both under‐coverage and self‐selection may lead to biased estimates. This paper describes these methodological problems. It also explores the effect of various correction techniques (adjustment weighting and use of reference surveys). This all leads to the question whether properly design web surveys can be used for data collection. The paper attempts to answer this question. It concludes that under‐coverage problems may solve itself in the future, but that self‐selection leads to unreliable survey outcomes.
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“The reliability and validity of web-based self-reported mental disorder symptom clusters remains ambiguous,71 certainly for the current population”
From Mental Disorder Symptoms among Public Safety Personnel in Canada (2018) · cites this paper as [71]
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“In contrast, the current rates may be inflated because of a self-selection bias of motivated responding by clinically symptomatic persons.71”
From Mental Disorder Symptoms among Public Safety Personnel in Canada (2018) · cites this paper as [71]
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Cites
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Cited by
Sorted by citations
Expectations of brilliance underlie gender distributions across academic disciplines
Leslie, S.-J., Cimpian, A., Meyer, M., & Freeland, E. (2015) · Science · doi:10.1126/science.1261375 · Cited by 1,516
Mental Disorder Symptoms among Public Safety Personnel in Canada
Carleton, R. N., Afifi, T. O., Turner, S., Taillieu, T., Duranceau, S., LeBouthillier, D. M., Sareen, J., Ricciardelli, R., MacPhee, R. S., Groll, D., et al. (2018) · The Canadian Journal of Psychiatry · doi:10.1177/0706743717723825 · Cited by 558
“In contrast, the current rates may be inflated because of a self-selection bias of motivated responding by clinically symptomatic persons.(71) That argument might be countered by notions that particularly symptomatic persons may also be less likely to participate in research.”
BackgroundThe role of urban green space for human well-being
Bertram, C., & Katrin Rehdanz, A. (2015) · Ecological Economics · doi:10.1016/j.ecolecon.2015.10.013 · Cited by 515
Associations between green/blue spaces and mental health across 18 countries
White, M. P., Elliott, L. R., Grellier, J., Economou, T., Bell, S., Bratman, G. N., Cirach, M., Gascón, M., Lima, M. L., Lõhmus, M., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-87675-0 · Cited by 557
Krieger, N. (2020) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040119-094017 · Cited by 411
“, mainly highly educated and affluent persons) (18, 22, 201).”
Background
Metadata
- Authors
- Bethlehem, J.
- Affiliations
- Centraal Bureau voor de Statistiek (NL)
- Corresponding author
- Bethlehem, Jelke
- Venue
- International Statistical Review
- Publisher
- Wiley
- Published
- 2010-08
- Volume
- 78
- Issue
- 2
- Pages
- 161-188
- ISSN
- 0306-7734 (ISSN-L)
- 1751-5823
- OpenAlex
- W2129332419
- Cited by
- 1,315
- References
- 37
- Citations by year
- 2026: 228 · 2025: 173 · 2024: 151 · 2023: 149 · 2022: 122 · 2021: 144 · 2020: 109 · 2019: 47 · 2018: 38 · 2017: 54 · 2016: 20 · 2015: 32 · 2014: 19 · 2013: 14 · 2012: 6
- FWCI
- 29.95
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Statistical Review (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Topics
- Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
- Physical Sciences › Mathematics › Statistics and Probability › Survey Sampling and Estimation Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Census and Population Estimation
- Keywords
- online surveys, selection bias, undercoverage, self-selection, internet access, survey design, participant recruitment
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