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Interest in Science: Response Order Effects in an Adaptive Survey Design

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The chapter covers a survey experiment on two kinds of response effects. Response order is analysed against the background of the prominent primacy/recency hypothesis in survey methodology. Since this hypothesis refers to unordered scales, a modified version is suggested for the case of ordinal scales. The use of four vs. five response categories represents a second experimental factor. The probit regression analysis confirms both the “modified primacy-effect hypothesis” and the “missing-equivalence hypothesis” on the use of four vs. five response categories. The experiment is embedded in an adaptive survey design. The data come from the “Bremen City-of-Science Survey” which was conducted in mixed – web and telephone – mode in the spring of 2016. For this survey, a probability sample of residents aged 18 + was drawn from the population register of the city of Bremen.

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The effects of unit non-response on survey errors are of great concern to researchers.However, direct assessment of non-response bias in survey estimates is rarely possible.Attempts are often made to adjust for the effects of non-response by weighting, but thisusually relies on the use of frame data or external population data, which are at bestmodestly correlated with the survey variables. This paper reports the development ofa method to collect limited survey data from non-respondents to personal interviewsurveys and a large-scale field test of the method on the British Crime Survey (BCS).The method is shown to be acceptable and low cost, to provide valid data, and to haveno detrimental effect on the main survey. The use of the resultant data to estimatenon-response bias is illustrated and some substantive conclusions are drawn for the BCS.
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Studiendesign. In Bremen und seine Ausstellungen. Wie die Bevölkerung Bremens ihre Stadt, ihr Interesse an der Wissenschaft und die Ausstellungsangebote in Bremen und Bremerhaven sieht
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Interesse an wissenschaftlichen Themen
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  • S Can
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Regression models for categorical and limited dependent variables
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