Web Survey Bibliography
Whereas the sample composition biases of web surveys have been discussed extensively for developed countries, studies for developing countries are scarce. This article helps to fill that gap by comparing similar non-probability-based web surveys (WEB) and probability-based face-to-face (F2F) surveys both to each other and to the labor force. An analysis of WageIndicator data on work and wages derived from surveys held in 2009–2013 in 10 developing countries (WEB-sample N = 9135; F2F-sample N = 14,659), shows that F2F samples resemble the labor force to a larger extent than web samples do. In both cases, individuals in their 20s and early 30s are overrepresented, and younger and older respondents are underrepresented. This trend is more pronounced in WEB than in F2F samples. However, the differences converge in countries with higher Internet usage. A comparison of the WEB and F2F samples shows that compositions differ greatly, with web respondents being younger, more often male, more often living alone, and higher educated, although these differences are smaller in countries with higher Internet usage. Given the cost differences between the two survey modes, one should nevertheless consider the potential of web surveys as an instrument to gain explorative insights, specifically when searching for individuals with particular characteristics.
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.