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Bayesian D‐optimal choice designs for mixtures

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Consumer products and services can often be described as mixtures of ingredients. Examples are the mixture of ingredients in a cocktail and the mixture of different components of travel time (e.g. in‐vehicle and out‐of‐vehicle travel time) in a transportation setting. Choice experiments may help to determine how the respondent's choice of a product or service is affected by the combination of ingredients. In such experiments, individuals are confronted with sets of hypothetical products or services and they are asked to choose the most preferred product or service from each set. However, there are no studies on the optimal design of choice experiments involving mixtures. We propose a method for generating optimal designs for such choice experiments and demonstrate the large increase in statistical efficiency that can be obtained by using an optimal design.
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Keywords: Choice experiment; Experimental design; Mixture co‐ordinate exchange algorithm; Mixture experiment; Multinomial logit model; Particle swarm optimization

Document Type: Research Article

Publication date: 2017-02-01

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