Web Survey Bibliography
This paper presents some considerations of data validity and consistency for conjoint measurement implemented on the Internet. The results from a large scale ‘mega-study’, with 3715 respondents across 21 studies (Crave It! ), reveals that the vast majority of modeled results from each of the studies are statistically significant, with high R2 values. The use of the R2 statistic to assess data quality (viz., respondent consistency) provides a way to better assess the quality of results on an individual respondent basis, after the study has been run.
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Web Survey Bibliography - Moskowitz, H. (6)
- Optimising the language of email survey invitations; 2008; Moskowitz, H., Martin, B.
- Concept articulation and web research: a case study using quali-quant methods; 2007; Moskowitz, H., Rabino, S., Beckley, J.
- Motivations to join What language do online panellists need to hear to volunteer?; 2006; Moskowitz, H., Gofman, A., Namiranian, L.
- Internet loyalty programs: Lessons learned for Internet-based development research; 2002; Moskowitz, H., Khubani, A., Stanley, J.
- Establishing data validity in conjoint: Experiences with Internet-based ‘mega-studies’; 2002; Moskowitz, H., Moskowitz, J., Beckley, J., Mascuch, T., Adams, J., Sendros, A., Keeling, C.
- Refinement of Web Question Techniques and Tools; 2000; Moskowitz, H., Gofman, A., Tungaturthy, P., Manchaiah, M., Cohen, D.