Web Survey Bibliography
The growth of online survey research has led to an increased demand for probability-based online panels. Several of such panels are established in Europe and in the USA. As probability-based online panels are being used by scientific institutions to collect data and make inferences about the target population, questions about the quality of such data continue to be raised. In this chapter we assess the quality of an offline-recruited probability-based online panel of Internet users in Germany. First we report the key performance measures of the recruitment and the online surveys. In the second step of the quality assessment we compare our data to other surveys. As benchmarks we use two population surveys: the German General Social Survey (ALLBUS 2010) and the German subsample of the fifth round of the European Social Survey (ESS 2010). Both of these sources contain the information on private Internet usage and thus allow us to compare the estimates from our panel with the estimates calculated for subsamples of Internet users from the reference surveys. Both demographic and attitudinal measures are considered. We assess the feasibility of post-stratification weighting to correct for noncoverage and nonresponse. Additionally, we assess the comparability of the three surveys in modeling social phenomena. This chapter provides insight into the quality of data collected via online panels and discusses the efficiency of probability-based online panels as means of data collection for scientific purposes.
Web survey bibliography - In M. Callegaro, R. Baker, J. Bethlehem, A. S. Göritz, J. A. Krosnick and P. J. Lavrakas (eds.): Online Panel Research: A Data Quality Perspective. John Wiley & Sons, Ltd, Chichester, UK (15)
- Validating respondents' identity in online samples; 2014; Baker, R., Miller, C., Kachhi-Jiwani, D., Lange, K., Wilding-Brown, L., Tucker, J.
- The relationship between nonresponse strategies and measurement error; 2014; Malhotra, N., Miller, J. M., Wedeking, J.
- Nonresponse and measurement error in an online panel; 2014; Roberts, C., Allum, N., Sturgis, P.
- Estimating the effects of nonresponses in online panels through imputation; 2014; Zhang, W.
- An empirical test of the impact of smartphones on panel-based online data collection; 2014; Drewes, F.
- Professional respondents in nonprobability online panels; 2014; Hillygus, D. S., Jackson, N. M., Young, M.
- Informing panel members about study results; 2014; Scherpenzeel, A., Toepoel, V.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- The untold story of multi-mode (online and mail) consumer panels; 2014; McCutcheon, A. L., Rao, K., Kaminska, O.
- Online panels and validity; 2014; Groenlund, K., Strandberg, K.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- A critical review of studies investigating the quality of data obtained with online panels based on...; 2014; Callegaro, M., Villar, A., Yeager, D. S., Krosnick, J. A.
- Online panel research: History, concepts, applications and a look at the future; 2014; Callegaro, M., Baker, R., Bethlehem, J., Goeritz, A., Krosnick, J. A., Lavrakas, P. J.
- Motives for joining nonprobability online panels and their association with survey participation behavior...; 2014; Keusch, F., Batinic, B., Mayerhofer, W.
- Improving web survey quality; 2014; Steinmetz, S., Bianchi, S. M., Tijdens, K. G., Biffignandi, S.