Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/66849
Year of Publication: 
2008
Citation: 
[Journal:] Journal of Choice Modelling [ISSN:] 1755-5345 [Volume:] 1 [Issue:] 1 [Publisher:] University of Leeds, Institute for Transport Studies [Place:] Leeds [Year:] 2008 [Pages:] 98-127
Publisher: 
University of Leeds, Institute for Transport Studies, Leeds
Abstract: 
This paper compares different types of simulated draws over a range of number of draws in generating Bayesian efficient designs for stated choice (SC) studies. The paper examines how closely pseudo Monte Carlo, quasi Monte Carlo and Gaussian quadrature methods are able to replicate the true levels of Bayesian efficiency for SC designs of various dimensions. The authors conclude that the predominantly employed method of using pseudo Monte Carlo draws is unlikely to result in leading to truly Bayesian efficient SC designs. The quasi Monte Carlo methods analysed here (Halton, Sobol, and Modifed Latin Hypercube Sampling) all clearly outperform the pseudo Monte Carlo draws. However, the Gaussian quadrature method examined in this paper, incremental Gaussian quadrature, outperforms all, and is therefore the recommended approximation method for the calculation of Bayesian efficiency of SC designs.
Subjects: 
experimental design
Bayesian efficiency
(quasi) Monte Carlo simulation
Gaussian quadrature
Creative Commons License: 
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Document Type: 
Article
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