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Partial profile paired comparison designs for avoiding information overload

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Design and Analysis of Experiments

The inclusion of many attributes makes a choice experiment more realistic. The price to be paid for this increased face validity is however that the respondents’ task becomes cognitively more demanding. In order to avoid negative side effects, such as fatigue or information overload, a common strategy is to employ partial profiles, which are incomplete descriptions of the available alternatives. This talk presents efficient designs for the situation where each choice set is a pair of partial profiles and where only the main effects of the attributes are to be estimated.

This talk is part of the Isaac Newton Institute Seminar Series series.

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