Web Survey Bibliography
Title Adjustments for non-telephone bias in random-digit-dialling surveys
Author Frankel, M. R., Srinath, K. P., Hoaglin, D. C.
Source Statistic In Medicine, 22, pp. 1611-1626
Year 2003
Access date 07.10.2005
Abstract Telephone surveys are widely used in the U.S.A. for the study of health-related topics. They are subject to 'coverage bias' because they cannot sample households that do not have telephones. Although only around 5 per cent of households do not have a telephone, rates of telephone coverage show substantial variation by geography, demographic factors and socio-economic factors. In particular, lack of telephone service is more common among households that contain ethnic and racial minorities or that have lower socio-economic status with fewer opportunities for access to medical care and poorer health outcomes. Thus, failure to adequately account for households without telephones in health surveys may yield estimates of health outcomes that are misleading, particularly in states with at least moderate telephone non-coverage. The dynamic nature of the population of households without telephones offers a way of accounting for such households in telephone surveys. At any given time the population of telephone households includes households that have had a break or interruption in telephone service. Empirical results strongly suggest that these households are very similar to households that have never had telephone service. Thus, sampled households that report having had an interruption in telephone service may be used also to represent the portion of the population that has never had telephone service. This strategy can lead to a reduction in non-coverage bias in random-digit-dialling surveys. This paper presents two methods of adjusting for non-coverage of non-telephone households. The effectiveness of these methods is examined using data from the National Health Interview Survey. The interruption-in-telephone-service methods reduce non-coverage bias and can also result in a lower mean squared error. The application of the interruption-in-telephone-service methods to the National Immunization Survey is also discussed. This survey produces estimates for the 50 states and 28 urban areas. The interruption-in-telephone-service estimates tend be slightly lower than estimates resulting from poststratification and from another non-coverage adjustment method. The results suggest that the reduction in bias is greatest for variables that are highly correlated with the presence or absence of telephone service.
Access/Direct link PubMed (abstract)
Year of publication2003
Bibliographic typeJournal article
Web Survey Bibliography - 2003 (396)
- Weighting methods; 2003; Kalton, G., Flores Cervantes, I.
- Web-based data collection; 2003; Tourangeau, R.
- Using Web-based surveys to conduct counseling research; 2003; Granello, D. H., Weathon, J. E.
- The science of asking questions; 2003; Schaeffer, N. C., Presser, S.
- The democratization of research; 2003; MacElroy, B.
- Response order effects – how do people read?; 2003; Duffy, B.
- Response latency methodology for survey research: Measurement and modeling strategies; 2003; Mulligan, K. et al.
- Respondent-generated intervals: Do they help in collecting quantitative data?; 2003; Lusinchi, D.
- Report of the results of the Asthma awareness survey; 2003
- Presidential approval. You're only as good as your rating scale; 2003; Thomas, R. K. et al.
- On the importance of importance: An examination of weighting evaluation ratings with importance ratings...; 2003; Thomas, R. K. et al.
- Maximum difference scaling: Improved measures of importance and preference for segmentation; 2003; Cohen, S. H.
- Introduction to survey quality; 2003; Biemer, P. P., Lyberg, L. E.
- Evaluation of the minimal important difference for the feeling thermometer and the St. George's...; 2003; Schunemann, H. J. et al.
- Determining the probability of selection for a telephone household in a random digit dial sample design...; 2003; Triplett, T. A., Abi-Habib, N.
- Documenting comparative surveys for secondary analysis; 2003; Mohler, P., Uher, R.
- Proceedings of the American Association for Public Opinion Research annual conference.; 2003; Triplett, T. A., Abi-Habib, N.
- Cognitive Aspects of Survey Measurement and Mismeasurement; 2003; Tourangeau, R.
- Effect of Alternative Data Collection Modes on Cooperation Rates and Data Quality; 2003; Brady, S. E., Stapleton, C. N., Bouffard, J. A., Imel, J. D.
- Collecting behavioural data using the world wide web: considerations for researchers; 2003; Rhodes, S. D., Bowie, D, A., Hergenrather, K. C.
- Repairing Tom Swift’s Electric Factor Analysis Machine; 2003; Preacher, K. J., MacCallum, R. C,
- ImageJ; 2003; Rasband, W.
- Make Way for Web Surveys; 2003; Bankston, K.
- Kognitive Prozesse und Antwortverhalten in einer Internet-Befragung; 2003; Fuchs, M.
- Comparison of E-mail, Fax, and Postal Surveys of Pediatricians; 2003; McMahon, S. R., Iwamoto, M., Massoudi, M. S., Yusuf, H. R., Stevenson, J. M., David, F., Chu, S. Y.,...
- Towards Standardisation of Survey Outcome Categories and Response Rate Calculations; 2003; Lynn, P., Beerten, R., Laiho, J., Martin, J.
- The Influence of Visual Layout on Scalar Questions in Web Surveys; 2003; Christian, L. M.
- Web Survey Mailer System; 2003; Barrios, E.
- Prepaid and promised incentives in Web surveys - An experiment; 2003; Bosnjak, M., Tuten, T. L.
- Conducting On-line Surveys in Software Engineering; 2003; Punter, T., Ciolkowski, M., Freimut, B., John, I.
- A pilot study of a computer-assisted cell-phone interview (CACI) methodology to survey respondents in...; 2003; Wilkins, C., Casswell, S., Barnes, H. M., Pledger, M.
- Internet Marketing Research: Recources and Techniques; 2003; Forrest, E.
- Data editing by respondents and data suppliers; 2003; Weir, P.
- The Seven E-learning Barriers Facing Employees; 2003; Mungania, P.
- Experiences in e-survey development for IS research: Lessons from the use of automated control tools; 2003; Scornavacca, E., Becker, J.L., Barnes, S. J.
- Survey Response Behavior Shirking in Internet and Telephone Surveys; 2003; VanBeselaere, C.
- Using Internet-based Surveys to Reach Hidden Populations: Case of Nonabusive Illicit Drug Users; 2003; Duncan, D., White, J., Nicholson, T.
- Design Issues in Web-Based Electronic Business Surveys; 2003; Nichols, E. M., Murphy, E. D., Norman K. L., Rivadeneira, A., Eaton, C.
- Changes to Editing Strategies when Establishment Survey Data Collection Moves to the Web; 2003; Anderson, A. E., Cohen, S. H., Murphy, E. D.., Nichols, E. M., Sigman, R. S., Willimack, D. K.
- Synthesis of Results from the Response Mode and Incentive Experiment; 2003; Casper, R., Shaw, K. A.
- A Test of a Bimodal Survey Model on the Cooperative Communicators Association: A case Study; 2003; Brashears, T., Bullock, S., Akers, C.
- The Infusion of Internet-Based Surveys and Postal Mail Surveys; 2003; McGlothlin, J. M.
- The design of Web surveys: Interactive and visual features of Web questionnaires; 2003; Tourangeau, R., Couper, M. P., Conrad, F. G.
- Web/Online Surveys; 2003; Burke, A.
- Data Editing By Reporting Enterprises; 2003; Anonymous
- Initiative and Clarification in Web-Based Surveys; 2003; Schober, M. F., Conrad, F. G., Ehlen, P., Lind, L. H., Coiner, T.
- Using Fine-Grained Likert Scales in Web Surveys; 2003; Mathieson, K., Doane, D. P.
- Was based questioning procedure; 2003; Batinic, B.
- Online-Erhebungen in den Sozialwissenschaften; 2003; Reips, U. -D.
- Psychologische Forschung zum und im Internet; 2003; Reips, U. -D.
