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Article

Accounting for attribute-level non-attendance in a health choice experiment: does it matter?

Details

Citation

Erdem S, Campbell D & Hole AR (2015) Accounting for attribute-level non-attendance in a health choice experiment: does it matter?. Health Economics, 24 (7), pp. 773-789. https://doi.org/10.1002/hec.3059

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

Journal
Health Economics: Volume 24, Issue 7

StatusPublished
Publication date31/07/2015
Publication date online05/05/2014
Date accepted by journal01/04/2014
URL
PublisherWiley-Blackwell
ISSN1057-9230
eISSN1099-1050

People (2)

Professor Danny Campbell

Professor Danny Campbell

Professor, Economics

Professor Seda Erdem

Professor Seda Erdem

Professor, Economics