期刊
出版社
HOGREFE & HUBER PUBLISHERS
DOI: 10.1027/1614-2241/a000014
关键词
factorial survey; experimental vignette design; fractional factorial design; confounded factorial design; ANOVA; multilevel analysis
Vignette studies use short descriptions of situations or persons (vignettes) that are usually shown to respondents within surveys in order to elicit their judgments about these scenarios. By systematically varying the levels of theoretically important vignette characteristics a large population of different vignettes is typically available - too large to be presented to each respondent. Therefore, each respondent gets only a subset of vignettes. These subsets may either be randomly selected in following the tradition of the factorial survey or systematically selected according to an experimental design. We show that these strategies in selecting vignette sets have strong implications for the analysis and interpretation of vignette data. Random selection strategies result in a random confounding of effects and heavily rely on the assumption of no interaction effects. In contrast, experimental strategies systematically confound interaction effects with main or set effects, thereby preserving a meaningful interpretation of main and important interaction effects. Using a pilot study on attitudes toward immigrants we demonstrate the implementation and analysis of a confounded factorial design.
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