Investigating Attribute Non‐attendance and Its Consequences in Choice Experiments With Latent Class Models

A growing literature, mainly from transport and environment economics, has started to explore whether respondents violate some of the axioms about individuals' preferences in Discrete Choice Experiments (DCEs) and use simple strategies to make their choices. One of these strategies, termed attribute non-attendance (ANA), consists in ignoring one or more attributes. Using data from a DCE administered to healthcare providers in Ghana to evaluate their potential resistance to changes in clinical guidelines, this study illustrates how latent class models can be used in a step-wise approach to account for all possible ANA strategies used by respondents and explore the consequences of such behaviours. Results show that less than 3% of respondents considered all attributes when choosing between the two hypothetical scenarios proposed, with a majority looking at only one or two attributes. Accounting for ANA strategies improved the goodness-of-fit of the model and affected the magnitude of some of the coefficient and willingness-to-pay estimates. However, there was no difference in the predicted probabilities of the model taking into account ANA and the standard approach. Although the latter result is reassuring about the ability of DCEs to produce unbiased policy guidance, it should be confirmed by other studies.