Optimal Designs for 2 k Choice Experiments

By Leonie Burgess, Deborah J. Street. 2003

106 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/293d64d7d8dad989969e5c420877bf05b1d29ec3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. John M. Rose
2. Jordan J. Louviere
3. David A. Hensher
4. Michiel C. J. Bliemer
5. Riccardo Scarpa
6. Peter Goos
7. Roselinde Kessels
8. Stephane Hess

In Management Science and Operations Research

1. Peter Goos
2. John M. Rose
3. Jordan J. Louviere
4. Martina Vandebroek
5. Michiel C. J. Bliemer
6. David A. Hensher
7. Roselinde Kessels
8. A. A. J. Marley

Citations in the corpus

• What You Don’t Know Might Hurt You: Some Unresolved Issues in the Design and Analysis of Discrete Choice Experiments (2006, methodology): “Statistical design theory now exists to optimize the efficiency of designs for generic conditional logit models, and alternative–specific conditional logit models (see e.g., Burgess and Street 2003, 2005a, b; Street and Burgess 2004; Street et al. 2001, 2005, forthcoming).”
• Heterogeneous Conjoint Choice Designs (2005, background): “Recent work in statistics has focused on the development of globally optimal designs for certain choice models (Burgess and Street 2003; Street, Bunch, and Moore 2001; Street and Burgess 2004).”
• Dissecting the Random Component of Utility (2002, background): “Severin varied design efficiency by varying the number of attribute level differences between pairs of options based on results in Street, Bunch and Moore (2001), who showed that statistical efficiency is a function of numbers of attribute level differences (see also Burgess and Street 2001).”
• Approximation of bayesian efficiency in experimental choice designs (2008, unknown): “In the first approach, researchers have made the strong assumption that all parameter priors for the design are simultaneously equal to zero (e.g., Burgess and Street 2003; Grasshoff and Schwabe 2006; Huber and Zwerina 1996; Street and Burgess 2004; Street et al. 2001).”
• Modeling the choices of individual decision-makers by combining efficient choice experiment designs with extra preference information (2008, methodology): “The designs developed by Burgess and Street (2003, 2005) and Street and Burgess (2004a,b, 2007) allow one to construct optimal or nearly optimal designs for generic DCEs, which in turn allow one to estimate generic CLMs of the general form shown in equation (5).”
• A Comparison of Criteria to Design Efficient Choice Experiments (2006, background): “Finally, Burgess and Street (2003) derive D-optimal choice designs for two-level attributes of any choice set size and extend these results in Burgess and Street (2005) to apply to attributes with any number of levels.”
• Households’ Willingness to Pay for Water Service Attributes (2005, unknown): “Street et al. (2001) and Burgess and Street (2004a) deal with attributes that take only two levels, such that structure among levels is not an issue.”