Cited by 1,315Survey Methodology and NonresponseSurvey Sampling and Estimation TechniquesCensus and Population Estimation

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Selection Bias in Web Surveys

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Bethlehem, Jelke·2010·International Statistical Review

DOI 10.1111/j.1751-5823.2010.00112.x

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Abstract

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 central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Statistical Analysis With Missing Data
Lahiff, M., Little, R. J. A., & Rubin, D. B. (1989) · Journal of the American Statistical Association · doi:10.2307/2289883 · Cited by 17,385
Statistical Analysis with Missing Data
Little, R. J. A., & Rubin, D. B. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/9781119013563 · Cited by 8,473
Internet, Mail, and Mixed-Mode Surveys: The Tailored Design Method
Dillman, D. A., Smyth, J. D., & Christian, L. M. (2008) · Cited by 5,345
A generalization of sampling without replacement from a finite universe
Horvitz, D. G., & Thompson, D. J. (1952) · Journal of the American Statistical Association · doi:10.1080/01621459.1952.10483446 · Cited by 4,293
Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
Rosenbaum, P. R., & Rubin, D. B. (1984) · Journal of the American Statistical Association · doi:10.1080/01621459.1984.10478078 · Cited by 3,082
A Generalization of Sampling Without Replacement From a Finite Universe
Horvitz, D. G., & Thompson, D. J. (1952) · Journal of the American Statistical Association · doi:10.2307/2280784 · Cited by 3,011
Web Surveys
Couper, M. P. (2000) · Public Opinion Quarterly · doi:10.1086/318641 · Cited by 2,086
On the Two Different Aspects of the Representative Method: The Method of Stratified Sampling and the Method of Purposive Selection
Neyman, J. (1934) · Journal of the Royal Statistical Society · doi:10.2307/2342192 · Cited by 1,086
The Effectiveness of Adjustment by Subclassification in Removing Bias in Observational Studies
Cochran, W. G. (1968) · Biometrics · doi:10.2307/2528036 · Cited by 961

Show all 37 references

Research works printed but not linked: 20

Bethlehem J.G., 1988, Reduction of the nonresponse bias through regression estimation, J. Official Statist., 4, 251
Bethlehem J.G., 2002, Survey Nonresponse
Bethlehem J.G., 2009, The Rise of Survey Sampling
Börsch‐Supan A., 2004, Correcting the Participation Bias in an Online Survey
Bowley A.L., 1926, Measurement of the precision attained in sampling, Bull. Int. Statist. Inst., 6
Cobben F., 2004, Nonresponse Correction Techniques in Household Surveys at Statistics Netherlands: a CAPI‐CATI Comparison
Cochran W.G., 1953, Sampling Techniques
Cochran W.G., 1977, Sampling Techniques
De Haan J., 2006, Jaarboek ICT en Samenleving, De Digitale Generatie
Eurostat, 2007, More than 40% of Households have Broadband Internet Access
Hansen M.H., 1953, Survey Sampling Methods and Theory
Kendall M.G., 1960, Where shall the history of statistics begin, Biometrika, 47, 447
Kiaer A. N., 1895, Observations et Expériences Concernant des Dénombrements Représentatives, Bull. Internat. Statist. Inst., 176
Kiaer A. N., 1997, Den Repräsentative Undersökelsesmetode, Christiania Videnskabsselskabets Skrifter. II. Historiskfilosofiske klasse, 4, 37
Kish L., 1967, Survey Sampling
Kuusela V., 2003, Proceedings of the 4th ASC International Conference, 317
10.1111/j.2397-2335.1934.tb04184.x · DOI
Scherpenzeel A., 2010, Social Research and the Internet: Advances in applied Methods and New Research Strategies
Terhanian G., 2001, Exploiting analytical advances: Minimizing the biases associated with Internet‐based surveys of non‐random samples, ESOMAR Publication Services, 248, 247
Vonk T., 2006, The effects of panel recruitment and management on research results, a study among 19 online panels, ESOMAR Publication Services, 317, 79

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“De manera más amplia, este tipo de muestreo puede no representar con precisión a la población objetivo (Bethlehem, 2010).”
Background
Speech-language pathologists’ experience with nursing initiated texture modified diets in health care settings
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The role of ownership inclination on the intention to subscribe to music streaming among older adults
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“…given this, it is expected that the findings from thai elder consumers can be applied to other elderly customers. the online survey approach was used because it can quickly reach a large sample to portray consumer opinion on some issues rapidly (Bethlehem, 2010) and is cost effective (Jason, 2012).”
Widening participation and enhancing academic success: the impact of university diplomas on non-traditional students’ academic lives
Nieuwoudt, J. E., Andrews, G., Quinn, R. K., & Syme, S. (2025) · Studies in the Education of Adults · doi:10.1080/02660830.2025.2463222 · Cited by 2
“However, it is difficult to determine the impact of any type of selection bias due to the information of non-participants not available, and comparisons between participants and non-participants are not feasible (Bethlehem 2010).”
AAPM WGWMRSC Report 420: chapter climate check: Mixed methods analysis of survey responses
Cetnar, A. J., Aldosary, G., Koo, M. C., Lincoln, H., Pérez-Andújar, A., Prajapati, S., Simiele, S. J., & Hendrickson, K. R. G. (2025) · Journal of Applied Clinical Medical Physics · doi:10.1002/acm2.14600 · Cited by 2
“9,10 Within this survey, we note that positive responses in the open-ended questions were either absent or brief, lacking speciﬁc details.”
The epicenter of conspiracy belief: The economically left‐leaning and culturally regressive spot in the political landscape
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“In order to diminish bias and measurement error occurring from online, non-probability sampling (Bethlehem, 2010; Hooghe & Teepe, 2007), the data have been weighted by post-stratification and iterative proportional fitting (see Rao et al., 2002; Valliant, 1993, which accounts for respondents’ age,…”
‘He’s Practising His Learned Social Skills on the Cat’: A Mixed-Methods Investigation of Parental Perspectives of the Role of Pets in Autistic Children’s Social Skills and Wellbeing
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“Although there are benefits to online research, it must be acknowledged that there was potential for self-selection bias (Bethlehem, 2010).”
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“Voluntary participation may have introduced self-selection bias (Bethlehem, 2010), with individuals who had more adverse experiences being more likely to respond to the optional open-ended questions and thus being potentially overrepresented (Redshaw et al., 2007).”
Selective attraction to shorter muzzles in dogs is a hidden driver of the brachycephalic welfare crisis
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Alternative selection mechanisms in online surveys
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“This includes individual usage styles, like posting on social media, and motivational factors (Bethlehem 2010).”
Influential
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“…a través de entrevistas personales es crítica para los propósitos de este estudio, ya que los métodos de recolección que se basan en tecnologías de la información (tales como paneles en línea o muestreo telefónico aleatorio) pueden producir estimaciones sesgadas del uso de TIC (Bethlehem 2010).”
Background
Revisiting Prostate Cancer Screening Practices Among Vermont Primary Care Physicians
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“Self-selection web surveys have been shown to yield results which suffer from significant bias, rendering conclusions drawn from such surveys questionable [12].”
Background
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“However, selection bias is expected to be prevalent for the online survey, as it is the case in most voluntary questionnaire-based studies (44, 45), which may have led to an overestimation of the equine community’s rather positive intention.”
Background
Mixed methods study protocol to explore acculturation, lifestyles and health of immigrants from the Community of Portuguese-Speaking Countries in two Iberian contexts: how to face uncertainties amidst the COVID-19 pandemic
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Kim, K.-S. (2021) · American Journal of Biomedical Science & Research · doi:10.34297/ajbsr.2021.14.002011 · Cited by 2
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“The under-representation of older individuals and those from lower-income households tends to be observed in web-based surveys ( 56 ) and is likely exacerbated by the focus on those with pre-pandemic ride-sourcing experience in this study.”
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“However, as Bethelehem (2010) shows, web surveys are increasingly replacing other formats, including face-to-face surveys, due to some advantages like low cost, agility to launch the survey and reduction of the time needed to treat data.”
Background
The correlations of BIS/BAS, SIS/SES-EF and SOI-R Questionnaires in two Czech samples: An implication for future national studies
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Problemas relacionados con las encuestas preelectorales desde una perspectiva comparada
Traugott, M. W. (2015) · Estudios Públicos · doi:10.38178/cep.vi138.205 · Cited by 2
Monitoring Health and Well-Being in Emerging Adults: Protocol for a Pilot Longitudinal Cohort Study
Lystad, R. P., Pulido, D. F., Peters, L., Johnstone, M., Ellis, L. A., Braithwaite, J., Wuthrich, V. M., Amin, J., Cameron, C. M., & Mitchell, R. J. (2020) · JMIR Research Protocols · doi:10.2196/16108 · Cited by 2
“Although self-selection can lead to unreliable survey outcomes [37], there are potential methods for correcting for selection biases (eg, poststratification or weighting class adjustments, propensity score adjustments, and generalized regression modelling [38]).”
Method
Is it all about knowledge? A survey of attitudes toward ADHD among German pediatricians
Fechner, M. E., Mazheika, Y., Fehr, F., Jung, R., & Borusiak, P. (2022) · Journal of Public Health · doi:10.1007/s10389-022-01758-4 · Cited by 2
“These are known to lead to insufficient data quality in voluntary online surveys (Bethlehem 2010).”
Background
Mixed-Use Urban Planning and Development
Kusumastuti, D., & Nicholson, A. (2017) · UC Research Repository (University of Canterbury) · Cited by 2
Conservative non-pharmacological management of knee osteoarthritis in Switzerland: a survey among medical specialistsPreprint
Ettlin, L., Nast, I., Huber, E. O., & Niedermann, K. (2020) · doi:10.21203/rs.2.20763/v1 · Cited by 2
The siren's song of anonymous web‐based sampling
Brasky, T. M., Krok‐Schoen, J. L., Conroy, S., Newton, A. M., Strassels, S. A., Hays, J. L., & Wagener, T. L. (2022) · Cancer · doi:10.1002/cncr.34097 · Cited by 2
“Although the authors note that the study is subject to several biases that are common to survey designs, they do not clarify that this study is especially subject to biases that are inherent in web- based convenience sampling, particularly when one is drawing from individual websites.(2,3) Indeed, the authors report a…”
Background
Variation in gaze understanding across the life span: A process-level perspectivePreprint
Prein, J. C., Maurits, L., Werwach, A., Haun, D. B. M., & Bohn, M. (2023) · doi:10.31234/osf.io/dy73a · Cited by 2

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
DOI: 10.1111/j.1751-5823.2010.00112.x
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
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
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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Selection Bias in Web Surveys

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