How well do discrete choice experiments predict health choices? A systematic review and meta-analysis of external validity
Matthew Quaife (),
Gian Luca Di Tanna and
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Fern Terris-Prestholt: London School of Hygiene and Tropical Medicine
Gian Luca Di Tanna: Queen Mary University of London
Peter Vickerman: University of Bristol
The European Journal of Health Economics, 2018, vol. 19, issue 8, 1053-1066
Abstract Discrete choice experiments (DCEs) are economic tools that elicit the stated preferences of respondents. Because of their increasing importance in informing the design of health products and services, it is critical to understand the extent to which DCEs give reliable predictions outside of the experimental context. We systematically reviewed the literature of published DCE studies comparing predictions to choices made in reality; we extracted individual-level data to estimate a bivariate mixed-effects model of pooled sensitivity and specificity. Eight studies met the inclusion criteria, and six of these gave sufficient data for inclusion in a meta-analysis. Pooled sensitivity and specificity estimates were 88% (95% CI 81, 92%) and 34% (95% CI 23, 46%), respectively, and the area under the SROC curve (AUC) was 0.60 (95% CI 0.55, 0.64). Results indicate that DCEs can produce reasonable predictions of health-related behaviors. There is a great need for future research on the external validity of DCEs, particularly empirical studies assessing predicted and revealed preferences of a representative sample of participants.
Keywords: Discrete choice experiment; External validity; Hypothetical bias; Meta-analysis (search for similar items in EconPapers)
JEL-codes: C59 I10 C83 (search for similar items in EconPapers)
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