A Comparison of Criteria to Design Efficient Choice Experiments
To date, no attempt has been made to design efficient choice experiments by means of the G- and V-optimality criteria. These criteria are known to make precise response predictions, which is exactly what choice experiments aim to do. In this article, the authors elaborate on the G- and V-optimality criteria for the multinomial logit model and compare their prediction performances with those of the D- and A-optimality criteria. They make use of Bayesian design methods that integrate the optimality criteria over a prior distribution of likely parameter values. They employ a modified Fedorov algorithm to generate the optimal choice designs. They also discuss other aspects of the designs, such as level overlap, utility balance, estimation performance, and computational effectiveness.
- DOI
- 10.1509/jmkr.43.3.409
- Volume
- 43 (3)
- Pages
- 409-419
- Language
- en
- Export
- BibTeX
- Sources
- crossref