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Improved Modelling of Interaction Effects in Discrete Choice Experiments
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Improved Modelling of Interaction Effects in Discrete Choice Experiments
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Journal Article
Improved Modelling of Interaction Effects in Discrete Choice Experiments
2022
Overview
Background: Discrete choice experiments (DCEs) are rarely analyzed with choice models that include a full set of two-way interactions between the attribute levels: the resulting model would be (too) difficult to interpret and the sample size requirements (far) beyond what is feasible in applied research. Therefore, an alternative modelling approach is introduced that allows for interactions between the attributes-as opposed to interactions between the attributes levels. Methods: DCEs often comprise at least a subset of attributes for which monotonically increasing or decreasing preferences can be presumed, e.g. costs, benefits, risks, etc. Without imposing linear preferences, an optimal scaling approach can be used to transform the levels of these attributes onto continuous latent scales, which can be interacted with each other and with the levels of categorical attributes. This results in a very parsimonious model specification. Results: The proposed model with and without interactions is fitted on an existing dataset of N = 3699 respondents who each completed 16 EQ-5D-3L discrete choice tasks. As shown, the interactions between the attributes are straight-forward to interpret and their inclusion greatly improves statistical (WAIC) model fit statistics, while requiring 97% fewer parameters compared to a standard MIXL model with a full set of 2-way interactions between the included levels. Conclusions: The proposed interaction model is parsimonious, produces estimates that are straight-forward to interpret, and accommodates the estimation of interactions in DCEs with more attractive and feasible sample size requirements. The model has one major disadvantage: it is not straight-forward to transform preferences for attributes with categorical levels onto a continuous latent scale.
Publisher
Springer Nature B.V
Subject
