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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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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“To mitigate self-selection bias, the strategies recommended by Bethlehem (2010) were applied, in which the study expanded the distribution of the survey using various social networks (SNSs) such as Facebook, Instagram, and LinkedIn, in addition to emails.”
Methodological approaches and author-reported limitations in evaluation studies of digital health technologies (DHT): A scoping review of DHT interventions for cancer, diabetes mellitus, and cardiovascular diseases
Gityamwi, N., Armes, J., Harris, J., Ream, E., Green, R., Ahankari, A. S., Callwood, A., Ip, A., Cockle‐Hearne, J., Grosvenor, W., et al. (2025) · PLOS Digital Health · doi:10.1371/journal.pdig.0000806 · Cited by 6
“…creating a sample that is not representative as participants recruited online are subject to greater self-selection and may disproportionately comprise people from a particular socio-economic group, technology savvy or those who are health conscious or motivated to seek health solutions [163,164].”
Association of recruitment pathways and response quality with farm and farmer characteristics within an online-survey among German livestock farmers
Mergenthaler, M., Kemnade, M., Ollier-Höppe, C., & Schröter, I. (2025) · International journal on food system dynamics · doi:10.1163/18696945-bja00001 · Cited by 5
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Lurtz, M., Archuleta, K. L., Kothakota, M. G., & Jorgensen, T. (2021) · Financial Planning Review · doi:10.1002/cfp2.1112 · Cited by 5
“Selection bias is not uncommon in survey data (Bethlehem, 2010), but it does present issues for the interpretation of results.”
Background
A Survey of Treatment Trends for Acute Quadriceps Tendon Ruptures Among North American Surgeons
Matthies, N.-F., Paul, R., Dwyer, T., Chahal, J., & Whelan, D. B. (2022) · Orthopaedic Journal of Sports Medicine · doi:10.1177/23259671211045399 · Cited by 5
“Web surveys have a potential for high nonresponse rates, which can lead to estimation error.(1) Lack of response may have been due to a lack of desire to participate in an online survey, a lack of interest in the subject matter, or a simple lack of involvement in the care of orthopaedic trauma or acute QTR.”
Background
EXAMINING THE IMPACTS OF TRUST AND CREATIVITY ON INNOVATION FOCUSED PROMOTIVE VOICE
Sabol, M. A., & Winton, B. G. (2022) · International Journal of Innovation Management · doi:10.1142/s1363919622500244 · Cited by 5
Journalistien painostus ja uhkailu Suomessa: yleisyys ja vaikutukset
Hiltunen, I., Suuronen, A., & Pöyhtäri, R. (2022) · Media & viestintä · doi:10.23983/mv.120278 · Cited by 5
“Korkea itsevalintavinouman riski yhdistettynä matalaan vastausprosenttiin vähentää merkittävästi mahdollisuuksia tehdä näytteen perusteella luotettavia yleistyksiä kaikista suomalaisista journalisteista (ks. Bethlehem 2010; Sivo ym.”
Background
Implementing evidence into clinical practice. A survey amongst Norwegian acupuncturists
Dahle, M. L., & Alræk, T. (2023) · European Journal of Integrative Medicine · doi:10.1016/j.eujim.2023.102234 · Cited by 5
The Battle against COVID-19 in Jordan: A cross-Sectional Study Assessing the Experience of Jordanians who have been Infected with COVID-19
Nassar, R. I., Thiab, S. H., & Basheti, I. A. (2023) · Pharmacy Practice · doi:10.18549/pharmpract.2023.1.2791 · Cited by 4
Willingness of Participation in an Application-Based Digital Data Collection among Different Social Groups and Smartphone User Clusters
Máté, Á., Rakovics, Z., Rudas, S., Wallis, L., Ságvári, B., Huszár, Á., & Koltai, J. (2023) · Sensors · doi:10.3390/s23094571 · Cited by 5
“The questionnaire included questions about the socio-demographic characteristics of the respondents, their attitudes towards various aspects of the digital world and their use of information and communication technology (ICT) devices.”
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Cavanagh, N., Shrubsole, K., Alsop, T., & Williams, K. (2023) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2023.05.012 · Cited by 5
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Cisel, M. (2023) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v24i4.7265 · Cited by 7
“Self-selection bias is inherent in online surveys (Bethlehem, 2010), but it did not impede comparisons within items or across age categories, as self-selection affected all groups equally.”
Background
Ethical Considerations for AI-Driven Adaptive Virtual Environments in XR Training for First Responders: An Industry Perspective
Zechner, O., Pretolesi, D., Jaespert, E., Guirao, D. G., & Tscheligi, M. (2023) · IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) · doi:10.1109/metroxraine58569.2023.10405605 · Cited by 6
“1) Sources of Bias in Data Collection and Advanced Analytics: (a) Selection bias: Occurs when the collected data is not representative of the target population, leading to biased results [22].”
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Berneri, C., Larcom, S. T., Peng, C., & She, P.-W. (2024) · European Journal of Law and Economics · doi:10.1007/s10657-024-09800-4 · Cited by 7
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“For this reason, we do not know the amount of people who received the survey, nor the characteristics of non-respondents, hence the potential nonresponse bias is unknown [24,37].”
The Role of Mega-events In Promoting Sustainable Behaviour: A Multi-group Analysis Using Micom
Alagarsamy, S., Mehrolia, S., & Ramdas, R. (2024) · International Journal of Hospitality & Tourism Administration · doi:10.1080/15256480.2024.2390612 · Cited by 5
“By assigning different weights to different groups within the sample, based on their prevalence in the target population, statistical weighting corrects for discrepancies in sample composition, aligning it more closely with the population characteristics (Bethlehem, 2010; Eysenbach & Wyatt, 2002).”
The scholarly and practice profile of respiratory therapists in Canada: A cross-sectional survey
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“Secondly, self-selection bias might mean that the participants were already interested in aspects of personal development and well-being, and that this sample does not accurately represent all managers in South Africa [98].”
Cultural Influence on Global Assessment of Higher Education Service Quality
Sultan, P., & Wong, H. Y. (2013) · IGI Global eBooks · doi:10.4018/978-1-4666-3966-9.ch024 · Cited by 5
Web Panels for Official Statistics
Bethlehem, J. G., & Cobben, F. (2013) · Cited by 5
Self-citation
Socioeconomic impact of migraine in Italy: Results of a national survey
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“As they were recruited via an online survey, this population may be biased towards the ability to use a computer or a mobile device with internet access (40).”
Background
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“The larger share of young respondents is common in web surveys, because older people are less likely to own a computer or an internet connection (Bethlehem, 2010) and in this instance be members of the survey company's online panel.”
Background
Clinical and Research Perspectives on Visual Scene Displays
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“while reaching out to people outside the researchers’ social networks (Bethlehem 2010).”
Background
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“Lastly, given the recruitment protocols used, the study is subject to selection bias [27], further highlighting the need to careful interpretation of study results.”
Method
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“This selection bias is crucial because people with limited access to the internet might not have been able to participate in the study (Bethlehem, 2010).”
Background
Locating Medical Information during an Infodemic: Information Seeking Behavior and Strategies of Health-Care Workers in Germany
Holzmann‐Littig, C., Stadler, D., Popp, M., Kranke, P., Fichtner, F., Schmaderer, C., Renders, L., Braunisch, M. C., Assali, T., Platen, L., et al. (2023) · Healthcare · doi:10.3390/healthcare11111602 · Cited by 5
“Furthermore, selection bias is a known issue in online surveys [60] and cannot be ruled out.”
Background
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Arrington, T. L., & Darabi, A. (2017) · Educational Technology Research and Development · doi:10.1007/s11423-017-9561-y · Cited by 5
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“In addition, the sample members were selfselected volunteers found through social websites and as such may tend to have similarly strong opinions compared to the rest of the population (Jelke Bethlehem, 2010).”
Background
Retracted
Nonprobability Sampling
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“This sampling approach may lead to selection bias (Bethlehem, 2010), potentially overrepresenting individuals with specific interests or characteristics.”
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“Online questionnaires provide access to a large group of respondents but may result in biased estimates as participants self-select to participate (Bethlehem, 2010).”
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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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