Web Survey Bibliography
The chapter aims to explore and evaluate in more detail the efficiency of the propensity score adjustment (PSA) and the power of webographic (i.e. behavioral and attitudinal) variables in adjusting biases arising from non-randomized sample selection. In this context, it is to be considered that evidence for the applicability of PSA in the field of surveys in the scientific community is very limited. The empirical application is based on the Dutch sample of the WageIndicator Survey for 2009 - a multi-country, continuous volunteer web survey devoted to the collection of labor-related variables. In the analysis, the target variable is the monthly gross wage. The sample is compared with a probability-based web sample from the LISS panel (Longitudinal Internet Studies for the Social Sciences) which is also used as a reference survey in the PSA application.
The findings indicate that with the availability of an accurate probability-based reference survey the application of PSA can help reducing biases in volunteer samples. With respect to the inclusion of webographic variables, at least for the target variable wages, the computed propensity weights did not lead to the expected improvements. This was also due to the fact that those propensity weights which effectively reduced the bias between the samples showed a much higher variability impacting on the validity of estimates. Nevertheless, and considering the advantages of volunteer web surveys (like reduced costs, flexibility, worldwide coverage, etc.) and their more and more extensive use, it is important to be aware of how far can weights improve the representativeness of nonprobability panels. The presented adjustment approaches seem to offer improvements with respect to bias correction which also allow for better generalizations of estimates from volunteer samples.
Web survey bibliography - Tijdens, K. G. (18)
- Self-identification of occupation in web surveys: requirements for search trees and look-up tables ; 2015; Tijdens, K. G.
- Identifying and correcting question-wording problems: the case of Wageindicator; 2015; Slavec, A., Vehovar, V., Tijdens, K. G.
- WEBDATANET: Innovation and Quality in Web-Based Data Collection ; 2014; Steinmetz, S., Slavec, A., Tijdens, K. G., Reips, U.-D., de Pedraza, P., Popescu, A., Belchior, A., ...,...
- Improving web survey quality; 2014; Steinmetz, S., Bianchi, S. M., Tijdens, K. G., Biffignandi, S.
- Targeting the bias – the impact of mass media attention on sample composition and representativeness...; 2014; Steinmetz, S., Oez, F., Tijdens, K. G.
- Exploring selection biases for developing countries - is the web a promising tool for data collection...; 2014; Tijdens, K. G., Steinmetz, S.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Dropout Rates and Response Times of an Occupation Search Tree in a Web Survey; 2014; Tijdens, K. G.
- WEBDATANET: A Network on Web-based Data Collection, Methodological Challenges, Solutions, and Implementation...; 2014; Tijdens, K. G., Steinmetz, S., de Pedraza, P., Serrano, F.
- Challenges and pitfalls of measuring wages via web surveys - some explorations; 2012; Steinmetz, S., Bianchi, A., Tijdens, K., Biffignandi, S.
- Understanding selection bias in a worldwide, volunteer web-survey; 2012; Tijdens, K., Steinmetz, S.
- Hrh remuneration: Comparing wage levels, ranking And dispersion of 16 occupations In the health workforce...; 2011; Tijdens, K., de Vries, D.
- Wages worldwide results and measurement issues from the multi-country. WageIndicator web-survey ; 2011; van Klaveren, M., Tijdens, K.
- Text string matching to measure occupations in web-surveys; 2011; Tijdens, K. G.
- Codebook and explanatory note on the WageIndicator dataset ; 2010; Tijdens, K., van Zijl, S., Hughie-Williams, M., van Klaveren, M., Steinmetz, S.
- Potentials and Constraints of Propensity Score Weighting to Improve Web Survey Quality; 2010; Steinmetz, S., Tijdens, K.
- Presentation of WEBSURVNET; 2009; de Pedraza, P., Steinmetz, S., Tijdens, K.
- Sample bias, weights and efficiency of weights in a continuous web voluntary survey; 2007; de Pedraza, P., Tijdens, K., de Bustillo, R.