Web Survey Bibliography
In the following five chapters, several methodological innovations in panel surveys are evaluated. In each chapter, one of the methods discussed above to study and correct for measurement errors will be used to study how these methodological innovations affect survey errors and/or substantive conclusions derived from these survey data. The techniques discussed in the different chapters all build on one or more of the basic methods, but describe and explore the techniques in far more detail. In Chapter 3, the technique of propensity score matching is used to study the effects a mixed‐mode respondent recruitment strategy for a survey. It shows how matching can be used to separate nonresponse error from measurement error in a mixed telephone and Internet survey. Separating the two enables us to study how differences between the samples that remain after correcting for nonresponse error persist: the mode effect. In Chapter 4, we turn to the technique of Dependent Interviewing (DI). Different versions of DI are experimentally compared and evaluated using a quasi‐simplex model. This chapter shows how DI and the extent of measurement error present in a survey question on income affects the reliability coefficient. Chapter 5 further explores the use of Dependent Interviewing in panel surveys. This chapter focuses on the effect DI has on substantive estimates that use income questions. Apart from this, details of a validation study using the same income questions shed light on how DI works to affect survey estimates. Chapter 6 focuses on the topic of change in attitude question in a population that experiences a period of life changes. A mixed‐method study that combines longitudinal survey data with qualitative interviews shows how attitudes change over time. Not only do levels of attitudes towards their study change among a group of first year psychology students, the concept of interest itself also changes. The chapter shows how the meaning of study motivation for students itself changes over time. The final chapter focuses on panel attrition. Recent advances in mixture Structural Equation Modeling are used to describe the process of attrition in a panel study with monthly measurements. The chapter shows how different archetypes of respondents drop out of a study in different ways and for different reasons. This chapter concludes by showing how every group of attriters affects longitudinal nonresponse error in a different way.
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Web survey bibliography - Thesis, diplomas (29)
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Designing web surveys for the multi-device internet; 2015; de Bruijne, M.
- Rating Scales in Web Surveys: A Test of New Drag-and-Drop Rating Procedures; 2015; Kunz, T.
- Mixed-method feasibility study comparing the outpatient assessment of burn patients using a tablet device...; 2015; Mitchell, S. S.
- Facebook, Twitter, & Qr Codes: An Exploratory Trial Examining The Feasibility Of Social Media Mechanisms...; 2014; Gu, L. L.
- Open-ended questions in Web Surveys-Using visual and adaptive questionnaire design to improve narrative...; 2014; Emde, M.
- Design and Implementation of an Online Questionnaire Tool; 2014; Schaniel, R.
- User Modeling via Machine Learning and Rule-Based Reasoning to Understand and Predict Errors in Survey...; 2013; Stuart, L. C.
- Investigation of background acoustical effect on online surveys: A case study of a farmers' market...; 2013; Tang, Xi.
- Developing a New Mixed-Mode Methodology For a Provincial Park Camper Survey in British Columbia; 2013; Dyck, B. W.
- Classifying Mouse Movements and Providing Help in Web Surveys; 2013; Horwitz, R.
- Satisficing in Web Surveys: Implications for Data Quality and Strategies for Reduction; 2013; Zhang, Che.
- “I think I know what you did last summer” Improving data quality in panel surveys; 2012; Lugtig, P. J.
- Analyzing Functionalities for Online Questionnaire System (OQS); 2012; Atown, H. Y.
- Web panels in Slovenia; 2011; Lenar, J.
- Clarifying Survey Questions; 2011; Redline, C. D.
- Nonresponse and Measurement Error in Mobile Phone Surveys ; 2010; Kennedy, C.
- Internet-Based Measurement With Visual Analogue Scales: An Experimental Investigation; 2010; Funke, F.
- Social Networking Sites: Evaluating and Investigating their use in Academic Research; 2010; Redmond, F.
- E-epidemiology : Adapting epidemiological methods for the 21st century; 2009; Bexelius, C.
- Visual Design Effects on Respondents’ Behavior in Web-Surveys; 2009; Greinoecker, A.
- Improving survey response in mail and internet general public surveys using address-based sampling and...; 2009; Messer, B. L.
- Design Variations in Adaptive Web Sampling; 2008; Vincent, K. S.
- Internet-based survey design for university web sites : a case study of a Thai university ; 2007; Vate-U-Lan, P.
- On the cost-efficiency of probability sampling based mail surveys with a Web response option; 2005; Werner, P.
- Cognitive Laboratory Experiences : On Pre-testing Computerised Questionnaires; 2002; Snijkers, G.
- (Non)Response bei Web-Befragungen; 2002; Bosnjak, M.
- Web survey errors; 2001; Lozar Manfreda, K.
- A study of factors affecting responses in electronic mail surveys; 1997; Good, K. P.