Title
Comparing different sampling schemes of approximating the integrals involved in the efficient design of stated choice experiments Comparing different sampling schemes of approximating the integrals involved in the efficient design of stated choice experiments
Author
Faculty/Department
Faculty of Applied Economics
Publication type
article
Publication
Oxford ,
Subject
Economics
Source (journal)
Transportation research: part B: methodological. - Oxford
Volume/pages
44(2010) :10 , p. 1268-1289
ISSN
0191-2615
ISI
000283695600007
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
The semi-Bayesian approach for constructing efficient stated choice designs requires the evaluation of the design selection criterion value over numerous draws taken from the prior parameter distribution assumed when generating the design. The semi-Bayesian D-criterion value of a design is then calculated as the average value of the D-errors over all the draws taken. The traditional way to take draws from a distribution is to use the Pseudo-Monte Carlo approach. However, other sampling approaches are available as well. Examples are Quasi-Monte Carlo approaches using Halton sequences, Faure sequences, modified Latin hypercube sampling and extensible shifted lattice points, a GaussHermite quadrature approach and a method using spherical-radial transformations. Not much is known in general about which sampling scheme is most efficient for calculating semi- Bayesian D-errors when constructing efficient stated choice designs. In this study, we compare the performance of these approaches under various scenarios and identify the most efficient sampling scheme for each situation. The method based on a spherical-radial transformation is shown to outperform the other methods when small numbers of draws are used.
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