Web Survey Bibliography
The objective of this work is to study, de ne and compare alternative sampling frames (population lists) for the representative population coverage as a base for sample selection in internet surveys. In addition, the study aims to provide a methodology for the domain adjustment procedures which enables to use the latest available information. There are several types of sampling frames such as target population frame and available list frame. The target population frames are the ideal frame, which cannot easily be obtained. On the other hand, total population list frames can be either household or individual unit based. The quality of the existing sampling frames can be can be dierent. The sampling frames may be; unde ned, ill de ned, partially de ned, or perfectly de ned.
The target population of the sample information collected from internet surveys (e-mail surveys & web surveys) faces many diculties in the identi cation of the possible sampling frame. For voluntary participation, one has to identify the coverage of the target population. Within the available data sources, special adjustments are proposed for the small domains. Some basic variables can be proposed for this purpose. Adjustments can be made for gender breakdown, age groups, and education groups. In terms of sample selection, the type of access to internet surveys can be based on several limitations. Early attempts was based on the restricted access designs for e-mail survey, or e-mail message followed with a web survey. As an alternative, voluntary participation designs became common for web surveys. In this type of design, observations are obtained through haphazard entry to the web survey questionnaire. Therefore, a probability sample cannot be obtained, due to unknown selection probabilities. Alternative data adjustment procedures for the case of voluntary participation is proposed in this study. Several types of weighted location estimators are proposed on the basis of these designs. For surveys having complex sample designs, a combined ratio mean (proportion, mean, or ratio) or separate ratio mean alternatives can be proposed. The overall selection probabilities for households can be determined by obtaining household based information from the population information for each domain. This information can be obtained by dividing the total population of each domain by the corresponding average household size for this domain. The overall selection probability of the domains will be their overall sampling fractions. From the previous experience with the
variability of the average household sizes in dierent domains, an alternative approach is also proposed. Due to the unavailability of the census data as Urban and Rural, it was decided to evaluate the available version as City (province centre & district centre) versus Village (sub-district centre & village).
In this study, alternative sampling frames are compared for their population coverage and representation for sample selection in internet surveys. The work also aims to provide a methodology for the domain adjustment procedures which also enables to eliminate the sample selection bias on the basis of the corrected information.
Conference homepage(abstract)
Web Survey Bibliography - Weighting & imputation (262)
- The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study; 2013; West, B. T.
- Improving Surveys with Paradata: Analytic Uses of Process Information; 2013; Kreuter, F.
- Ten questions to ask your online survey provider; 2013; Williams, D.
- Practical tools for designing and weighting survey samples; 2013; Valliant, R. L., Daver, J. A., Kreuter, F.
- Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys; 2013; Steinmetz, S., Raess, D., Tijdens, K., de Pedraza, P.
- Moving an established survey online – or not?; 2013; Barber, T., Chilvers, D., Kaul, S.
- The comparison of road safety survey answers between web-panel and face-to-face; Dutch results of SARTRE...; 2013; Goldenbeld, C., de Craen, S.
- Measuring working conditions in a volunteer web survey; 2013; de Pedraza, P., Villacampa, A.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.
- The rise of the "connected viewer"; 2012; Smith, A., Boyles, J. L.
- Eurobarometer Special surveys: Special Eurobarometer 381; 2012
- Computation of Survey Weights: Bridging Theory and Practice; 2012; Debell, M.
- Modes of Data Collection; 2012; Tourangeau, R.
- An experimental investigation of the effects of noncontingent and contingent incentives in recruiting...; 2012; Lavrakas, P. J., Dennis, J. M., Peugh, J., Shand-Lubbers, J., Lee, E., Peugh, J., Charlebois, O., Murakami...
- Rules of engagement: The war against poorly engaged respondents - guidelines for elimination; 2012; Gittelman, S. H., Trimarchi, E.
- Web Panels; 2012; Bethlehem, J., Biffignandi, S.
- Use of Response Propensities; 2012; Bethlehem, J., Biffignandi, S.
- Weighting Adjustment Techniques; 2012; Bethlehem, J., Biffignandi, S.
- The Problem of Self-Selection; 2012; Bethlehem, J.,Biffignandi, S.
- The Problem of Undercoverage; 2012; Bethlehem, J., Biffignandi, S.
- Respondent-driven sampling; 2012; Schonlau, M., Liebau, E.
- A Structural Analysis Based on Similarity between Fuzzy Clusters and Its Application to Evaluation Data...; 2012; Chiba, R., Furutani, T., Sato-Ilic, M.
- Why one should incorporate the design weights when adjusting for unit nonresponse using response homogeneity...; 2012; Kott, P. S.
- Cell Sample Demographics under Alternative Dual-Frame Sample Designs; 2012; Montgomery, R., Morrison, H., Zeng, W., Wolter, K., Blumberg, S. J., O'Connor, K.
- Data Quality from Low Cost Data Collection Methodologies; 2012; Traugott, M. W.
- To Weight, or Not to Weight, That is the Question: Survey Weights and Multivariate Analysis; 2012; Young, R., Johnson, D. R.
- Multiple Imputation for Unit Nonresponse and Measurement Error; 2012; Peytchev, A.
- Assessing the Quality of Survey Data ; 2012; Blasius, J.
- Collecting, Managing, and Assessing Data Using Sample Surveys; 2012; Stopher, P.
- Online survey research: Findings, best practices, and future research. Report prepared for the Advertising...; 2011; Vannette, D.
- Online survey research: Findings, Best practices, and future research; 2011
- Just published: Forrester Wave™ of enterprise feedback management satisfaction and loyalty solutions...; 2011; McInnes, A.
- In search of a new approach to measure newspaper audiences in Canada: The journey continues; 2011; Crassweller, A. et al.
- Households with Computers, Telephone Subscriptions, and Internet Access, Selected Years, 1997 - 2010; 2011
- Eurobarometer Special surveys: EB75.1 E-Communications Household Survey. Special Eurobarometer 362; 2011
- A meta-analysis of experiments manipulating progress indicators in Web surveys; 2011; Callegaro, M., Villar, A., Yang, Y.
- The Evolution of Edits in the Canadian Census of Population Online Questionnaires; 2011; Laroche, D.
- Current Projects at University of Ljubljana; 2011; Lozar Manfreda, K.
- Maintaining Cross-Sectional Representativeness in a Longitudinal General Population Survey ; 2011; Lynn, P.
- The German Access Panel and the Impact of Response Propensities; 2011; Amarov, B., Enderle, T., Muennich, R., Rendtel, U., Zins, S.
- A Bayesian analysis of small area probabilities under a constraint; 2011; Nandram, B., Sayit, H.
- The Impact of Non-Response Treatments on the Stability of Blockmodels; 2011; Znidarsic, A., Ferligoj, A., Doreian, P.
- Research on Internet survey errors and control methods; 2011; Mingyue, F., Xicang, Z.
- Separation of selection bias and mode effect in mixed-mode survey – Application to the face-to...; 2011; Bayart, C., Bonnel, P.
- Social Climate Survey of Tobacco Control: A mixed-mode approach; 2011; Klein, J. D., McMillen, R.
- Exploring use of information in paradata through calibration method to detect and adjust non-response...; 2011; Billiet, J. Matsuo, H.
- Assessment of propensity score methods on nonresponse bias adjustment; 2011; Alanya, A., Billiet, J., Matsuo, H.
- Nonsampling errors in dual frame telephone surveys ; 2011; Brick, J. M., Flores Cervantes, I., Lee, S., Norman, G.
- Handbook of Nonresponse in Household Surveys ; 2011; Bethlehem, J., Cobben, F., Schouten, B.
- Dropout in Web-based studies: Methodology; 2011; Reips, U. -D.
