How well do discrete choice experiments predict health choices? A systematic review and meta-analysis of external validity

Matthew Quaife*, Fern Terris-Prestholt, Gian Luca Di Tanna, Peter Vickerman

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

43 Citations (Scopus)
275 Downloads (Pure)

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.

Original languageEnglish
Number of pages14
JournalEuropean Journal of Health Economics
Early online date29 Jan 2018
DOIs
Publication statusE-pub ahead of print - 29 Jan 2018

Keywords

  • Discrete choice experiment
  • External validity
  • Hypothetical bias
  • Meta-analysis

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