Accounting for Attribute-Level Non-Attendance in a Health Choice Experiment: Does it Matter?

Abstract

An extensive literature has established that it is common for respondents to ignore attributes of the alternatives within choice experiments. In most of the studies on attribute non-attendance, it is assumed that respondents consciously (or unconsciously) ignore one or more attributes of the alternatives, regardless of their levels. In this paper, we present a new line of enquiry and approach for modelling non-attendance in the context of investigating preferences for health service innovations. This approach recognises that non-attendance may not just be associated with attributes but may also apply to the attribute's levels. Our results show that respondents process each level of an attribute differently: while attending to the attribute, they ignore a subset of the attribute's levels. In such cases, the usual approach of assuming that respondents either attend to the attribute or not, irrespective of its levels, is erroneous and could lead to misguided policy recommendations. Our results indicate that allowing for attribute-level non-attendance leads to substantial improvements in the model fit and has an impact on estimated marginal willingness to pay and choice predictions.

Keywords: attribute non-attendance; attribute-level non-attendance; discrete mixture logit; discrete-choice experiments; health service innovations.