Web Survey Bibliography
Many surveys today are affected by high nonresponse. This can be a serious problem to survey quality since nonresponse causes systematic error (bias) in the survey estimates. 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 this problem, nor efficient. Measures need to be taken also at the data collection stage. In this direction, different forms of responsive design have recently been proposed. The general objectives of responsive design have been formulated in Groves and Heeringa (2006). The main idea underlying this method is to intervene in the data collection process, in order to achieve an ultimate set of responding units that is “better balanced” or “more representative” than if no special effort is made. Interventions are settled by evaluating the sample properly as the data collection unfolds. To this purpose different indicators have been proposed, such as the balance and representativity indicators of the set of respondents and the distance between respondents and nonrespondents (Särndal, 2011, Schouten et al., 2009, Schouten et al., 2011, and Lundquist and
Särndal, 2012). These indicators are computable from selected auxiliary variables, which are known for the responding units as well as for the non-responding ones. By monitoring the indicators during the data collection process, it is possible to modify the original design during the course of the data collection, in order to obtain a better balanced ultimate response set. The recent existing literature presents many progresses in the development of this methodology. However, further investigations are needed in order to apply it in practice, also to different contexts. The aim of this paper is to evaluate the potentials of responsive design in the framework of mixed mode panels, where one mode is Web. The empirical application uses data from the on-going probability-based PAADEL panel. The PAADEL-Producer panel is an Italian regional panel of businesses in the agro-food sector managed at the CASI centre of Bergamo University. The recruitment of the panel was conducted in 2012 and lasted approximately three months. The first step recruitment was based on phone mode (maximum number of contact attempts five); the second step recruitment was based on the mixed mode approach (Web, phone, mail, fax). Using the
database of data collection of this research, first the progression of the estimates of a few variables is studied as the data collection unfolds. Next the balance and representativity of the panel are investigated at different steps of the recruitment. Finally, a set of experimental responsive designs based on alternative interventions in the data collection is artificially reproduced. Results are analyzed in a comparative way to evaluate the impact of this approach on the final estimates. Special attention is devoted to the bias reduction issue. Some thoughts on the consequences on the variability of the estimates are also proposed. The results obtained are promising. By way of example, Table 1 shows some of the results that will be described in the study.
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Web survey bibliography (4086)
- Developing a New Mixed-Mode Methodology For a Provincial Park Camper Survey in British Columbia; 2013; Dyck, B. W.
- Mode effect analysis and adjustment in a split-sample mixed-mode Web/CATI survey; 2013; Kolenikov, S., Kennedy, C.
- Exploring factors associated with respondent mode choice for surveys using mobile devices.; 2013; Walton, L.
- Responsive design for mixed-mode panel data; 2013; Bianchi, A., Biffignandi, S.
- Adjusting for bias in a mixed-mode CAWI survey on University students ; 2013; Clerici, R., Giraldo, A.
- Comparative analysis of data from web and face-to-face surveys. A case study on e-commerce in young...; 2013; Cappello, C., Pellegrino, D.
- Insights into Action Profiling shopping occasions for retailers through mobile and online research; 2013; Churkina, O., Morris, T.
- Mobilizing your Branded Panel: Panel data quality during the smartphone transition; 2013; Kugel, C., Brien, D., Blechman, J.
- Evaluating the left‐right dimension: Category Selection Probing conducted in an online access...; 2013; Huefken , V.
- From Face‐to‐face to Web: Consequences for Measurement of Complex and Open‐ended Questions...; 2013; Villar, A., Fitzgerald, R., Martin, P., Harrison, E., Gatrrell, L.
- An Examination of the Relationship Between Pretest Method Results and Data Quality; 2013; Maitland, A.
- Associations Between Interactional Indicators of Problematic Questions and Systems for Coding Question...; 2013; Dykema, J., Schaeffer, N. C., Garbarski, D.
- The Technology Behind Mobile Research: Browsers vs. Apps ; 2013; Macer, T.
- Methodological, legal and technical perspectives on the feasibility of web survey paradata in German...; 2013; Sattelberger, S.
- An imputation approach for analyzing mixed-mode surveys; 2013; Kim, J. K., Park, Se., Kim, S. Y.
- Investigating the Bias of Alternative Statistical Inference Methods in Sequential Mixed-Mode Surveys; 2013; Suzer-Gurtekin, Z., Heeringa, S. G., Valliant, R. L.
- Random versus Systematic Error in a Mixed Mode Online-Telephone Survey; 2013; Hox, J., Scherpenzeel, A., Boeve, A., Boeve, A., de Leeuw, E. D.
- Impact of mode design on reliability in longitudinal data; 2013; Cernat, A.
- Mobility and Smartphones: a pilot study of travel data collection among experienced and inexperienced...; 2013; Douhou, S., Scherpenzeel, A.
- Mobile devices a way to recruit hard-to-reach groups? Results from a pilot study comparing desk top...; 2013; Toepoel, V., Lugtig, P. J.
- The Relation of Survey Topic and Participation Behavior. Analyzing Unit Nonresponse using web-generated...; 2013; Zillmann, D., Schmitz, A., Blossfeld, H. P.
- Exploring patterns of academic usage: A Google Scholar based study of ESS, EVS, WVS and ISSP academic...; 2013; Malnar, B.
- Adding Observation to Copy Testing with Kids; 2013; Hurley, B., Salo, M.
- Web questionnaires in official population surveys: Do's and don'ts First experiments and impacts...; 2013; Blanke, K.
- Gamified Surveys: Journey Into Product Development; 2013; Adamou, B.
- Phish Rising: How Internet Criminals are Undermining the Viability of Online Survey Research…and...; 2013; Kunovic, K.
- Möglichkeiten zur impliziten Messung von Emotionen am Beispiel webcambasierter Gesichtsausdruckserkennung...; 2013; Wachenfeld, A., Moentmann, A., Bernet, F.
- Mode effects in Labour Force Surveys - do they really matter?; 2013; Koerner, T.
- Identifying and Mitigating Satisficing in Web Surveys: Some Experimental Evidence; 2013; Rossmann, J.
- Does left still feel right? The optimal position of answer boxes in Web surveys - revisited; 2013; Lenzner, T., Kaczmirek, L.,Galesic, M.
- Latent legitimacy: joint effects of religious orientation on the association between values and acceptance...; 2013; Henseler, A. K., Siegers, P., Beckers, T.
- Identifying Satisficing Respondents in Web Surveys: A Comparison of Different Response Time-Based Approaches...; 2013; Rossmann, J.
- Comparison of quality of web survey and CATI data using unobtrusive response latencies; 2013; Mayerl, J.
- A walking exercise on a tightrope: trying to balance coverage, probabilistic sampling and the costs...; 2013; Poggio, T.
- Comparability of substantive results between modes and incentive conditions in a probability-based telephone...; 2013; Pekari, N.
- Data Collection Method Comparisons for the 2011 Fishing, Hunting, and Wildlife-Associated Recreation...; 2013; Herbstritt, M., Hornick, D.
- Trends in Dutch egalitarian attitudes, 1975-2010: An age-period-cohort analysis; 2013; Meuleman, B., Oorschot, W. V.
- Comparing Questionnaire Pretesting Methods for the 2015 Population and Housing Census of Korea; 2013; Park, Y.
- Mixed Methods in Cognitive Interviewing: An analysis of the Russian version of the Schwartz Value Survey...; 2013; Efremova, M., Panyusheva, T.
- A mixed methods approach to investigate how Cognitive Interviewing findings can improve the validity...; 2013; Padilla, J. L., Miller, K., Loeb, M.
- Validity of Measuring Educational Attainment - Education and Value Orientation in the European Values...; 2013; Ortmanns, V.
- The comparability of Don't Know answers between CATI and CAWI modes; 2013; Pohjanpaa, K., Jarvensivu, M.
- Measuring the same concepts in several modes in the "BIBB/BAuA-Employee-Survey 2011/12" ; 2013; Gensicke, M., Tschersich, N., Hartmann, J.
- Error Prevention through Interviewer Emulation? Introducing questionnaire dialogues in the Norwegian...; 2013; Gravem, D. F.
- Multiple Group Confirmatory and Exploratory Factor Analysis: Exploring Measurement Invariance by Rotational...; 2013; Asparouhov, T.
- BSEM Measurement Invariance Analysis; 2013; Muthen, B. O.
- Does It Pay Off to Include Non-Internet Households in an Internet Panel? ; 2013; Leenheer, J., Scherpenzeel, A.
- ReCal OIR: Ordinal, Interval, and Ratio Intercoder Reliability as a Web Service; 2013; Freelon, D. G.
- Classifying Mouse Movements and Providing Help in Web Surveys; 2013; Horwitz, R.
- Old versus New: The Comparative Efficiency of Mail and Internet Surveys of State Legislators.; 2013; Fisher, S. H., Herrick, R.