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Web Survey Bibliography

Title Responsive Design for Web Panel Data Collection
Year 2013
Access date 23.05.2013

Many surveys today are affected by high nonresponse. This can be a detriment to survey quality since nonresponse causes systematic error (bias) in the estimates. A related problem is the need of survey costs reduction. Given the decreasing trend in response rates and the corresponding increasing resources needed to achieve preset response rates, taking measures only at the estimation stage is no more sufficient to overcome these problems. Measures need to be taken also at the data collection stage. In this direction, different forms of responsive design have been proposed (Groves and Heeringa, 2006, Särndal, 2011). The purpose of this paper is to study responsive design in the framework of Web panel data collection. This method of data collection is increasingly widespread for general population opinion evaluation and it allows disposing of many variables on the participation process. We explore whether this amount of information could be exploited in the framework of responsive design. We evaluate as well whether this method improves the estimates in terms of bias reduction and assess the consequences on the variability of the estimates. The empirical application uses data from two on-going probability-based household panels: the PAADEL panel (Italian panel for the agro-food sector) and the LISS panel (Dutch panel managed by CentERdata, Tilburg University). Using these databases, we artificially reproduce a set of experimental responsive designs based on alternative interventions in the data collection. Results are analyzed in a comparative way to evaluate the impact of this approach on the final estimates. Bibliography: Groves, R.M., and Heeringa, S.G. (2006), Responsive design for household surveys: tools for actively controlling survey errors and costs. Journal of the Royal Statistical Society: Series A, 169.Särndal, C.E. (2011), The 2010 Morris Hansen Lecture: Dealing with Survey Nonresponse in Data Collection, in Estimation. Journal of Official Statistics, 27, 1-21

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Year of publication2013
Bibliographic typeConferences, workshops, tutorials, presentations
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