Framework of Effective Sample Size Model for Stated Preference Experiment
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O213.2

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    Abstract:

    The stated preference (SP) method is a way to study people’s preferences through experiment design, often implemented with discrete choice models to estimate the parameters. This paper focuses on deriving the effective sample size for SP experiments which guarantees accurate parameter estimations by proposing an easy-to-operate and comprehensive framework. By applying the framework on an empirical study, a linear model is estimated which reveals that the number of factors and levels, scale of parameters, sample size, and the experimental design strategy have significant impacts on the accuracy of parameters. The effective sample size estimation models of three design strategies are obtained, based on which some practical principles for SP experiment design are proposed.

    Reference
    [1] Louviere J, Hensher D, Swait J. Stated Choice Methods: Analysis and Applications[M]. NewYork: Cambridge University Press, 2000.
    [2] Mcfadden D. Conditional Logit Analysis of Qualitative Choice Behavior[M]. Frontiers in Econometrics, Zarembka P, New York:Academic Press, 1974, 105-142.
    [3] Train K E. Discrete Choice Methods with Simulation[M]. Cambridge, UK: Cambridge University Press, 2003.
    [4] Rose J M, Bliemer M C J. Sample size requirements for stated choice experiments[J]. Transportation. 2013, 40(5): 1021-1041.
    [5] Rose J M, Bliemer M C J, Hensher D A, et al. Designing efficient stated choice experiments in the presence of reference alternatives[J]. Transportation Research Part B. 2008, 42(4): 395-406.
    [6] Orme B. Sample size issues for conjoint analysis studies[J]. Sawthooth Software Research paper Series Squim, WA, USA: Sawthooth Software Inc, 1998.
    [7] Johnson R F, Orme B K. Sample size issues for conjoint analysis[J]. Getting started with conjoint analysis: strategies for product design and pricing research. Madison: Research Publishers LLC, 2010: 57-66.
    [8] Chrzan K, Orme B. An overview and comparison of design strategies for choice-based conjoint analysis[R]. Sawtooth Software, Inc., 2000.
    [9] Bunch D S, Louviere J J, Anderson D. A comparison of experimental design strategies for multinomial logit models: The case of generic attributes[Z]. University of California, Davis, 1996,60.
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ZHU Wei, YANG Jiazhi. Framework of Effective Sample Size Model for Stated Preference Experiment[J].同济大学学报(自然科学版),2019,47(11):1670~1675

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History
  • Received:September 13,2018
  • Revised:August 27,2019
  • Adopted:July 28,2019
  • Online: December 05,2019
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