|Appears in Collections:||Economics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Including opt-out options in discrete choice experiments: issues to consider|
|Citation:||Campbell D & Erdem S (2019) Including opt-out options in discrete choice experiments: issues to consider. Patient, 12 (1), pp. 1-14. https://doi.org/10.1007/s40271-018-0324-6|
|Abstract:||Background: Providing an opt-out alternative in discrete choice experiments can often be considered to be important for presenting real-life choice situations in different contexts, including health. However, insufficient attention has been given to how best to address choice behaviours relating to this opt-out alternative when modelling discrete choice experiments, particularly in health studies. Objective: The objective of this paper is to demonstrate how to account for different opt-out effects in choice models.We aim to contribute to a better understanding of how to model opt-out choices and show the consequences of addressing the effects in an incorrect fashion.We present our code written in the R statistics program so that others can explore these issues in their own data. Methods: In this practical guideline, we generate synthetic data on medication choice and use Monte Carlo simulation. We consider three different definitions for the opt-out alternative and four candidate models for each definition. We apply a frequentist-based multimodel inference approach and use performance indicators to assess the relative suitability of each candidate model in a range of settings. Results: We show that misspecifying the opt-out effect has repercussions for marginal willingness to pay estimation and the forecasting of market shares. Our findings also suggest a number of key recommendations for DCE practitioners interested in exploring these issues. Conclusions: There is no unique best way to analyse data collected from discrete choice experiments. Researchers should consider several models so that the relative support for different hypotheses of opt-out effects can be explored.|
|Rights:||This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. This is a post-peer-review, pre-copyedit version of an article published in The Patient - Patient-Centred Outcomes Research. The final authenticated version is available online at: https://doi.org/10.1007/s40271-018-0324-6|
|Campbell-Erdem-ThePatient2018.pdf||Fulltext - Accepted Version||313.69 kB||Adobe PDF||View/Open|
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.