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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Couper, M. P. (2000) · Public Opinion Quarterly · doi:10.1086/318641 · Cited by 2,086
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
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
Cited by
Sorted by citations
Items 901–1,000 of 1,000
Abe, A. K. (2024) · Social Indicators Research · doi:10.1007/s11205-024-03418-4 · Cited by 1
“However, the possibility of other sampling biases remains (Bethlehem, 2010).”
Unterfrauner, E., Fabian, C., Hemming, G., & Garćıa, B. (2024) · Open Research Europe · doi:10.12688/openreseurope.17436.1 · Cited by 4
“The limitations of the data lie in the fact that, as with all voluntary participation, the dataset is limited to only those people who took the time to complete the questionnaire and thus represents a self-selected sample (Bethlehem, 2010).”
Lambrechts, H. A., Stoof, C. R., Garcia, M. D. P., Ludwig, F., & Paparrizos, S. (2024) · Climate Risk Management · doi:10.1016/j.crm.2024.100672 · Cited by 1
Janzen, L., Putz, F., Kaufhold, M., Straub, K., & Hollick, M. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714324 · Cited by 1
“…to complete our questionnaire might introduce a bias against non-panelists, it facilitated steering our study sample towards representativeness for smartphone users from major German cities regarding gender, age, education, and income, thus preventing sampling and selection biases [11, 48].”
The development and validation of the Social Attributions for Mental Illness (SAMI) scale
Huggard, L., Nearchou, F., & O’Connor, C. (2025) · PLoS ONE · doi:10.1371/journal.pone.0324592 · Cited by 2
“…offers advantages over traditional convenience samples, such as greater participant attentiveness and broader demographic diversity [34], this method of recruitment may have introduced potential sample limitations, such as underrepresentation of hard-to-reach samples and self-selection bias [35].”
The science of cuteness: where teddy bears’ beauty, comfort and care converge
Blanc, N., Tribot, A.-S., Brassac, T., & Mouquet, N. (2025) · The Journal of Positive Psychology · doi:10.1080/17439760.2025.2538890 · Cited by 1
“We acknowledge that this may be related to a self-selection bias, in which the selection process relies on individuals’ decision to participate in the survey (Bethlehem, 2010).”
Gooßen, K., Weise, A., Hirschmüller, A., Joisten, C., Jaax, S., Kreutz, C., Könsgen, N., & Breuing, J. (2025) · Clinical and Public Health Guidelines · doi:10.1002/gin2.70032 · Cited by 1
Surma, S., Lewandowski, Ł., Momot, K., Sobierajski, T., Lewek, J., Okopień, B., & Banach, M. (2025) · Nutrients · doi:10.3390/nu17172728 · Cited by 1
“The study was quantitative, cross-sectional and was conducted by the CAWI (Computer-Assisted Web Interviewing) method using an original online questionnaire [27].”
Pérez-Barbería, F. J., & Bodas, R. (2025) · Sustainability · doi:10.3390/su17188189 · Cited by 1
Norman, R., Campbell, R., Rowen, D., Viney, R. C., Street, D. J., Müller, F., Mercieca‐Bebber, R., Pickard, A. S., Cella, D. F., Shaw, J. W., et al. (2025) · The European Journal of Health Economics · doi:10.1007/s10198-025-01844-w · Cited by 1
“Although online panels provide convenient economical sampling frames and represent a popular sam - pling choice in modern science, potential selection biases deserve further research [61].”
Guerrant, M. T. (2014) · NCSU Libraries Repository (North Carolina State University Libraries) · Cited by 1
A Proposal for Mapping IT Professionals' Competence Supported by Multiple Intelligences Theory
Ferreira, F. R., & de Almeida, J. R. (2017) · International Journal of Human Capital and Information Technology Professionals · doi:10.4018/ijhcitp.2018010101 · Cited by 1
Webster, L. (2018) · puntOorg International Journal · doi:10.19245/25.05.pij.3.1/2.03 · Cited by 1
“One of the primary non-random sampling technique for which it is impossible to ‘construct unbiased estimates’, thus raising questions about the accuracy and rigor of the research (Bethlehem, 2010: 162).”
BackgroundSelbstwertprofile und ihre Korrelate im Lern- und Leistungskontext: Eine latente Profilanalyse
Kärchner, H., & Schwinger, M. (2018) · Zeitschrift für Pädagogische Psychologie · doi:10.1024/1010-0652/a000224 · Cited by 1
Ellenbroek, V., Meijers, M. J., & Krouwel, A. P. M. (2019) · Government and Opposition · doi:10.1017/gov.2019.30 · Cited by 1
Wilson-Ounekeo, R. C., & Lamp, W. O. (2020) · Journal of Medical Entomology · doi:10.1093/jme/tjaa129 · Cited by 1
“Online surveys require less money and time to deploy but have the drawback of self-selection (Bethlehem 2010), in that surveys are only completed by respondents who find them and are interested in the topic.”
Takao, M., Maki, Y., & Suzuki, T. (2021) · Psychogeriatrics · doi:10.1111/psyg.12688 · Cited by 1
Bégin, N. B., Boislard, M.-A., & Otis, J. (2021) · Sexologies · doi:10.1016/j.sexol.2021.03.002 · Cited by 1
Vivere da soli in una grande città durante il Covid-19. Esiti di una ricerca condotta a Milano
Civenti, G. (2021) · WELFARE E ERGONOMIA · doi:10.3280/we2021-001015 · Cited by 1
Walia, S. K., Jasrotia, A., Kour, P., & Choudhary, P. (2021) · Tourism Review International · doi:10.3727/154427221x16317419620200 · Cited by 1
Pandemi Sürecinde Sağlık Kaygısının Boylamsal İncelenmesi ve Yaşam Doyumu ile İlişkisi
ŞENOL, A. (2022) · Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi · doi:10.32709/akusosbil.950345 · Cited by 1
The COVID-19 Psychological Distress Scale (CPDS-16): Development and initial validation
Verma, S., Sahni, S. P., Pandehy, K. K., & Griffiths, M. D. (2022) · Journal of Concurrent Disorders · doi:10.54127/tzsj4223 · Cited by 1
Job Satisfaction, Life Satisfaction and the Unemployed Spouse
Anchustigui, J. (2016) · ScholarWorks (Walden University) · Cited by 1
Quality Assurance in Risk Management
Dykman, A. (2016) · doi:10.26686/wgtn.20387988 · Cited by 1
“Contacts Sampling errors can arise from the specific selection of participants (Bethlehem, 2010; Couper, 2000; Wang & Doong, 2007).”
BackgroundFathers’ perinatal mental health: Impacts, interventions and supports
Rominov, H. (2017) · Research Bank (Australian Catholic University) · doi:10.26199/acu688 · Cited by 1
Physical activity and health climate as predictors of work-related outcomes
Montgomery, A. J. (2017) · Figshare · Cited by 1
On Determining the Value of Online Customer Satisfaction Ratings – A Case‐based Appraisal
Freeman, J. (2020) · doi:10.1002/9781119721871.ch10 · Cited by 1
Early adopters of geospatial technologies for teaching geography in Australian secondary schools
Coleman, B. (2018) · UTAS Research Repository · doi:10.25959/23238473 · Cited by 1
The effectiveness of risk assessments in informing decision makers
Peace, C. (2019) · doi:10.26686/wgtn.17142020 · Cited by 1
Bayes, C. (2010) · doi:10.18297/etd/85 · Cited by 1
“This researcher could not control the selection process (Bethlehem, 2010).”
MMOG players' sense of place in virtual worlds
Alvarez, K. (2021) · doi:10.32657/10356/154528 · Cited by 1
Malden, D. E., Tartof, S. Y., Ackerson, B. K., Hong, V. X., Skarbinski, J., Yau, V., Qian, L., Fischer, H. J., Shaw, S. F., Caparosa, S. L., et al. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4075842 · Cited by 1
REMOVED DUE TO POLICY VIOLATIONSPreprint
Booth, H. L., Mourato, S., & Milner‐Gulland, E. J. (2022) · doi:10.31219/osf.io/9gzy3 · Cited by 1
de Vaus, D. (2013) · doi:10.1093/obo/9780199756384-0106 · Cited by 1
Pham, T. T. (2021) · doi:10.32469/10355/93239 · Cited by 1
An improved habitat suitability index for the great crested newtPreprint
Seccombe, E., & Salguero‐Gómez, R. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.15.520292 · Cited by 1
A Difference-in-Differences Approach for Estimating Survey Mode EffectsPreprint
Ollerenshaw, T. (2023) · doi:10.33774/apsa-2023-p5r6j
A Difference-in-Differences Approach for Estimating Survey Mode EffectsPreprint
Ollerenshaw, T. (2023) · doi:10.33774/apsa-2023-p5r6j-v2
A Difference-in-Differences Approach for Estimating Survey Mode EffectsPreprint
Ollerenshaw, T. (2023) · doi:10.33774/apsa-2023-p5r6j-v3
Evans, H., & Hislop, P. D. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4663909 · Cited by 1
Amoozegar-Montero, A. (2024) · doi:10.26686/wgtn.25215968 · Cited by 1
ONLINE QUESTIONNAIRES AND ONLINE DATA COLLECTION: REVIEW AND PRACTICAL RECOMMENDATIONS
Memon, M. A., Ramayah, T., Ting, H., & Cheah, J. (2026) · Journal of Applied Structural Equation Modeling · doi:10.47263/jasem.10(2)01 · Cited by 1
Florentin, A., & Rice, K. (2026) · Journal of Substance Use and Addiction Treatment · doi:10.1016/j.josat.2026.209912
Ethnic Identity and the Perception of Facial Profile Aesthetics: A Preliminary Study
Glasser, P. M. (2012) · Scholarship@Western (Western University)
Self-Regulated Learning, Motivation and Emotions Towards University Study. A Latent Class ApproachPreprint
Giraldo, A., & Meggiolaro, S. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2461608
“This controlled quota sample and the mixed-mode invitations avoided any high level of bias due to self-selection, a common problem in CAWI surveys (Bethlehem 2010).”
Vietnam towards the Maritime Labour Convention, 2006 : benefits, challenges and reality
Son, N. V. H. (2014) · Maritime Commons The Digital Repository of World Maritime University (World Maritime University)
Gap in Trade Companies’ Perception of Consumers’ Purchasing Processes
Gąsior, M., & Skowron, Ł. (2014) · Contemporary Management Research · doi:10.7903/cmr.12323
“Due to the fact that the study was concerned with Internet users, it should be noted that the selection of the study group by probabilistic sampling was very difficult, if not impossible (Furrer and Sudharshan, 2001; Bethlehem, 2010).”
BackgroundResearch Article British Public Opinion after a Decade of War: Attitudes to Iraq and Afghanistan
Gribble, R., Wessely, S. C., Klein, S., Alexander, D. M., Dandeker, C., & Fear, N. T. (2014)
Transgender, the Possibility of Adding a Third Gender Option
Prinsloo, D., & Ferreira, E. J. (2012) · Unisa Institutional Repository (University of South Africa)
Tan, B.-K., Burnett, A., Hallett, J., Ha, A. S. C., & Briggs, A. M. (2016) · Journal of Back and Musculoskeletal Rehabilitation · doi:10.3233/bmr-160658
“While online data collection modes may be feasible for such enquiry, particularly for sampling younger cohorts and those in non-urban settings, selection bias and low recruitment rates present logistic barriers that need consideration in this context [50,51].”
A Method for Measuring Online Audiences
Koehler, J., Skvortsov, E., & Vos, W. (2013)
Crippa, F., Zenga, M., & Mariani, P. (2019) · doi:10.1002/9781119579465.ch10
On Bias Adjustments for Web Surveys
Fan, L., Lou, W. Y. W., & Landsman, V. (2014)
Factors Influencing the Success of Permission-Based E-Mail Marketing Websites
Lin, H., Li, H.-T., & Wang, Y. (2017) · Advances in business strategy and competitive advantage book series · doi:10.4018/978-1-5225-2668-1.ch015
Environmental scanning practices in South African top performing companies
Tarpeh, T. (2017) · UpSpace Institutional Repository (University of Pretoria)
A emergência de uma nova dimensão cultural: as eleições holandesas de 2017
Otjes, S., & Krouwel, A. P. M. (2017) · Relações Internacionais · doi:10.23906/ri2017.56a03
Web 2.0 in agribusiness companies: An explanatory model of Its background and consequences
López-Becerra, E. I. (2017) · doi:10.31428/10317/6982
Leuteritz, J. (2019) · Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona)
KRNC: New Foundations for Permissionless Byzantine Consensus and Global Monetary StabilityPreprint
Ehrlich, C., & Guzova, A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1909.07433
“[8] The honor is supposed to be bestowed on the top example of Dutch literature published in a given year.”
BackgroundFactors Affecting Health Care Access among Transgender People in the United States
Kcomt, L. (2019) · Scholarship at UWindsor (University of Windsor)
On the nomological net of (non-)workaholic subtypes
Ontrup, G., & Patrzek, J. (2019) · Career Development International · doi:10.1108/cdi-12-2018-0327 · Cited by 1
The impact of technological change on survey nonresponse and measurement
Herzing, J. M. E. (2018) · MADOC (University of Mannheim)
Covering the last mile - A study on bikesharing integration with public transportation in Oslo
Anderson, E. (2019) · NORA - Norwegian Open Research Archives
Internet Penetration and Voting Advice Applications
Andreadis, I., Wall, M., & Krouwel, A. P. M. (2015) · Data Archiving and Networked Services (DANS)
Methods of Researching Online Communities
Jemielniak, D. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198839705.003.0003
Beyond Academia: Examining the Versatile Career Paths of PhDs
Etmanski, B. (2020) · UWSpace (University of Waterloo)
Selected Problems of Quality Assessment in Internet Surveys – a Statistical Perspective
Kupis-Fijałkowska, A. (2020) · Acta Universitatis Lodziensis Folia oeconomica · doi:10.18778/0208-6018.349.03
“Hence, there is no chance those units can be con‑ tacted and interviewed (Bethlehem, 2010).”
BackgroundMethodInfluentialKhyabani, E., & Louise, A. N. (2020) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)
Integrating Different Data Sources for Estimation of Total with Unknown Population Size
Liu, Z. (2020) · SMU Scholar (Southern Methodist University)
Rup, J. (2020) · UWSpace (University of Waterloo)
Saelim, K., Uthairat, M., Ruangnapa, K., Prasertsan, P., & Anuntaseree, W. (2021) · The Turkish Journal of Pediatrics · doi:10.24953/turkjped.2021.01.008
“87 Working place Community-based hospital 128 18 (17,20) 6 (5,6) 6 (5,6) 7 (7,8) Teaching hospital 147 19 (18,20) 6 (5,6) 6 (5,6) 8 (7,8) Unknown 32 19 (18,20) 6 (5,6) 6 (5,6) 8 (7,9) P = 0.”
BackgroundRhinoceros horn and Traditional Chinese Medicine: demand in China
Cheung, H. (2021) · The University of Queensland · doi:10.14264/debb833
Mandalapu, A. (2021) · Minds at UW (University of Wisconsin)
An evaluation of knowledge translation in the South African primary healthcare setting
Myburgh, M. (2013) · UpSpace Institutional Repository (University of Pretoria)
Zhilyaev, D., Cimpan, C., Cao, Z., Liu, G., Askegaard, S., & Wenzel, H. (2020) · Resources Conservation & Recycling X · doi:10.1016/j.rcrx.2020.100043
Retractedde Resende, M. A. C., Videira, R. L. D. R., da Costa, A. C. F. B., Silva, L. S. F., Rodrigues, M. F. D. O., & Assad, A. R. (2022) · Revista Eletrônica Acervo Saúde · doi:10.25248/reas.e9593.2022
Lee, Y., & Park, H. I. (2022) · Korean Journal of Industrial and Organizational Psychology · doi:10.24230/kjiop.v35i1.1-27 · Cited by 1
David, M. (2022) · Research Square · doi:10.21203/rs.3.rs-1421137/v1
A emergência de uma nova dimensão cultural: as eleições holandesas de 2017
Otjes, S., & Krouwel, A. P. M. (2017) · Relações Internacionais · doi:10.23906/ri2017.56
Gambacorta, R., Conte, M. L., Murgia, M., Neri, A., Rizzi, R., & Zanichelli, F. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3212611
Interações, C. D. R. R. (2016) · Interações (Campo Grande) · doi:10.20435/interacoes.v13i1.299
Biffignandi, S., & Bethlehem, J. G. (2021) · doi:10.1002/9781119371717.ch14
Self-citationWhere is home: Foster and kin carer's perceptions of their role
Harding, L. F. (2020) · Queensland University of Technology · doi:10.5204/thesis.eprints.204191
Jemielniak, D. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198839705.003.0001
Jemielniak, D. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198839705.003.0005
Lemmel, F. K., Jones, R., Johnson, S., Jolly, A., Miller, M., & Henderson, C. (2020) · doi:10.21203/rs.3.rs-30125/v1
Furlan, R., & Martone, D. (2011) · Wiley eBooks · doi:10.1002/9781119961154.ch6
Jemielniak, D. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198839705.003.0002
How interjections increase customer satisfaction, purchase intent and loyalty
Sheehan, B. T. (2022) · Queensland University of Technology · doi:10.5204/thesis.eprints.232832
Chan, S. (2022) · Victoria University of Wellington Law Review · doi:10.26686/vuwlr.v53i2.7708
Home Monitoring of the Carotid Arteries Using a Mobile Auscultation Device with App
Müller, I., Henze, J., Burmann, A., Salvi, R., Friebe, M., & Baum, R. (2022) · Current Directions in Biomedical Engineering · doi:10.1515/cdbme-2022-1139
Benvenuto, M., Sambati, F. V., & Viola, C. (2022) · MECOSAN · doi:10.3280/mesa2022-121oa13858
Wang, L., Yu, J., Chen, D., & Yang, L. (2022) · doi:10.32920/21440826
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review