Web Survey Bibliography
Title Internet and Smartphone Coverage in a National Health Survey: Implications for Alternative Modes
Author Couper, M. P.; Kelley, J.; Axinn, W.; Guyer, H.; Wagner, J.; West, B. T.
Year 2015
Access date 22.08.2016
Abstract
The rise of Internet-enabled smartphones presents an opportunity to re-examine the issue of Internet coverage and its implications for coverage bias. While a number of papers have examined cell phone coverage and Internet coverage separately, few have looked at the possible compensatory effects of joint coverage. We added two interviewer observations (one on Internet access and the other on smartphone ownership among respondents) to the National Survey of Family Growth (NSFG) with a view to exploring the feasibility of Internet-based follow-up surveys. NSFG is a national probability survey of women and men age 15-44, using a continuous design. We examine 8 quarters (2 years) of data, from September 2012 to August 2014.
Overall, we find that 82.2% of respondent report Internet access and 76.1% report having a smartphone (estimates weighted for differential selection and nonresponse). Combined, this means that 89.4% have access to the Internet, either via traditional devices or via a smartphone. We also find some evidence of compensatory coverage when looking at key gender/race/age subgroups. For instance, while Black male teens (15-17) have the lowest rate of Internet access (74.9%) and the lowest rate of smartphone usage (58.9%), when combined 82.6% have some form of Internet access.
We propose to examine the socio-demographic correlates of Internet and smartphone (and combined) coverage (access) in this population. In addition, we propose to look at the effect of differential coverage on key estimates produced by the NSFG, related to fertility, family formation, and sexual activity. While this does not address nonresponse bias issues related to alternative modes, our paper has implications for possible coverage biases that may arise in switching to a Web-based mode of data collection, either for follow-up surveys or to replace the main face-to-face data collection.
Overall, we find that 82.2% of respondent report Internet access and 76.1% report having a smartphone (estimates weighted for differential selection and nonresponse). Combined, this means that 89.4% have access to the Internet, either via traditional devices or via a smartphone. We also find some evidence of compensatory coverage when looking at key gender/race/age subgroups. For instance, while Black male teens (15-17) have the lowest rate of Internet access (74.9%) and the lowest rate of smartphone usage (58.9%), when combined 82.6% have some form of Internet access.
We propose to examine the socio-demographic correlates of Internet and smartphone (and combined) coverage (access) in this population. In addition, we propose to look at the effect of differential coverage on key estimates produced by the NSFG, related to fertility, family formation, and sexual activity. While this does not address nonresponse bias issues related to alternative modes, our paper has implications for possible coverage biases that may arise in switching to a Web-based mode of data collection, either for follow-up surveys or to replace the main face-to-face data collection.
Access/Direct link FCSM Research Conference Homepage (Abstract) / (Full text)
Year of publication2015
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - Noncoverage & sampling (851)
- Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not...; 2017; Toepoel, V.; Emerson, H.
- Nonresponses as context-sensitive response behaviour of participants in online-surveys and their relevance...; 2017; Wetzlehuetter, D.
- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- Pushing to web in the ISSP; 2017; Jonsdottir, G. A.; Dofradottir, A. G.; Einarsson, H. B.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- A test of sample matching using a pseudo-web sample; 2017; Chatrchi, G., Gambino, J.
- A Partially Successful Attempt to Integrate a Web-Recruited Cohort into an Address-Based Sample; 2017; Kott, P. S., Farrelly, M., Kamyab, K.
- Nonprobability sampling as model construction; 2017; Mercer, A. W.
- Enhancing survey participation: Facebook advertisements for recruitment in educational research; 2017; Forgasz, H.; Tan, H.; Leder, G.; McLeod, A.
- Determinants of polling accuracy: the effect of opt-in Internet surveys; 2017; Sohlberg, J.; Gilljam, M.; Martinsson, J.
- Article Establishing an Open Probability-Based Mixed-Mode Panel of the General Population in Germany...; 2017; Bosnjak, M.; Dannwolf, T.; Enderle, T.; Schaurer, I.; Struminskaya, B.; Tanner, A.; Weyandt, K.
- PC, phone or tablet? Use, preference and completion rates for web surveys ; 2017; Brosnan, K.; Gruen, B.; Dolnicar, S.
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- Standard Definitions Final Dispositions of Case Codes and Outcome Rates for Surveys; 2016
- Integration of a phone-based household travel survey and a web-based student travel survey; 2016; Verreault, H.; Morency, C.
- Du kommst hier nicht rein: Türsteherfragen identifizieren nachlässige Teilnehmer in Online-Umfragen; 2016; Merkle, B.; Kaczmirek, L.; Hellwig, O.
- Estimation and Adjustment of Self-Selection Bias in Volunteer Panel Web Surveys ; 2016; Niu, Ch.
- Geht’s auch mit der Maus? – Eine Methodenstudie zu Online-Befragungen in der Jugendforschung...; 2016; Heim, R.; Konowalczyk, S.; Grgic, M.; Seyda, M.; Burrmann, U.; Rauschenbach, T.
- FocusVision 2015 Annual MR Technology Report; 2016; Macer, T., Wilson, S.
- Can Student Populations in Developing Countries Be Reached by Online Surveys? The Case of the National...; 2016; Langer, A., Meuleman, B., Oshodi, A.-G. T., Schroyens, M.
- Comparisons of Online Recruitment Strategies for Convenience Samples: Craigslist, Google AdWords, Facebook...; 2016; Antoun, C., Zhang, C., Conrad, F. G., Schober, M. F.
- Comparing Cognitive Interviewing and Online Probing: Do They Find Similar Results?; 2016; Meitinger, K., Behr, D.
- Feature phones no barrier to conducting an effective conjoint study ; 2016; de Rooij, R.; Dossin, R.
- Patient preference: a comparison of electronic patient-completed questionnaires with paper among cancer...; 2016; Martin, P.; Brown, M.C.; Espin‐Garcia, O.; Cuffe, S.; Pringle, D.; Mahler, M.; Villeneuve, J.;...
- Device use in web surveys: The effect of differential incentives; 2016; Mavletova, A. M.; Couper, M. P.
- A look into the challenges of mixed-mode surveys; 2016; Klausch, L. T.
- The use of online social networks as a promotional tool for self-administered internet surveys; 2016; de Rada, V. D.; Arino, L. V. C; Blasco, M. G
- Assessing the Accuracy of 51 Nonprobability Online Panels and River Samples: A Study of the Advertising...; 2016; Yang,Y.;Callegaro,M.;Yang,Y.;Callegaro,M.;Chin,K.;Yang,Y.;Villar,A.;Callegaro, M.; Chin, K.; Krosnick...
- Estimated-control Calibrated Estimates from Nonprobability Surveys; 2016; Dever, J. A.
- Decomposing Selection Effects in Non-probability Samples ; 2016; Mercer, A. W.; Keeter, S.; Kreuter, F.
- Non-Observation Bias in an Address-Register-Based CATI/CAPI Mixed Mode Survey; 2016; Lipps, O.
- Bees to Honey or Flies to Manure? How the Usual Subject Recruitment Exacerbates the Shortcomings of...; 2016; Snell, S. A., Hillygus, D. S.
- Establishing the accuracy of online panels for survey research; 2016; Bruggen, E.; van den Brakel, J.; Krosnick, J. A.
- When will Nonprobability Surveys Mirror Probability Surveys? Considering Types of Inference and Weighting...; 2016; Pasek, J.
- Mixing modes of data collection in Swiss social surveys: Methodological report of the LIVES-FORS mixed...; 2016; Roberts, C.; Joye, D.; Staehli, M. E.
- What is the gain in a probability-based online panel to provide Internet access to sampling units that...; 2016; Revilla, M.; Cornilleau, A.; Cousteaux, A-S.; Legleye, S; de Pedraza, P.
- Representative web-survey!; 2016; Linde, P.
- Assessing targeted approach letters: effects in different modes on response rates, response speed and...; 2016; Lynn, P.
- The Analysis of Respondent’s Behavior toward Edit Messages in a Web Survey; 2016; Park, Y.
- The Utility of an Online Convenience Panel for Reaching Rare and Dispersed Populations; 2016; Sell, R.; Goldberg, S.; Conron, K.
- Setting Up an Online Panel Representative of the General Population The German Internet Panel; 2016; Blom, A. G.; Gathmann, C.; Krieger, U.
- Implementation of Web-Based Respondent Driven Sampling among Men Who Have Sex with Men in Sweden; 2016; Stroemdahl, S.; Lu, X.; Bengtsson, L.; Liljeros, F.; Thorson, A.
- Options for Fielding and Analyzing Web Surveys; 2016; Schonlau, M.; Couper, M. P.
- Report of the Inquiry into the 2015 British general election opinion polls; 2016; Sturgis, P., Baker, N., Callegaro, M., Fisher, St., Green, J., Jennings, W., Kuha, J., Lauderdale, B...
- Participant recruitment and data collection through Facebook: the role of personality factors; 2016; Rife, S. C.; Cate, K. L.; Kosinski, M.; Stillwell, D.
- Online Surveys are Mixed-Device Surveys. Issues Associated with the Use of Different (Mobile) Devices...; 2016; Toepoel, V.; Lugtig, P. J.
- Electronic and paper based data collection methods in library and information science research: A comparative...; 2016; Tella, A.
- The Validity of Surveys: Online and Offline; 2016; Wiersma, W.
- Computer-assisted and online data collection in general population surveys; 2016; Skarupova, K.
- Sunday shopping – The case of three surveys; 2016; Bethlehem, J.