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Important Stated Preference Experimental Design Issues in Recent Transportation Applications

机译：近期运输应用中的重要陈述偏好实验设计问题

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The paper discusses how the experimental design methods discussed in the preceding chapters, along with other methodological advances, can be used to address areas where SP techniques most need to be improved to deal with particular transportation contexts that are most prevalent in policy applications. Portfolio designs may be useful when people may make a series of choices in a repeating context, such as the mode used to go to work on different days of the week. The paper encourages the use of split sample approaches, where a certain experimental design variation is used for one randomly selected subsample, and one or more other design approaches are tested for other subsamples, allowing the effect of the experimental design on the responses to be tested. This approach can be used for different instructions about how respondents should think about the options, such as in the 'cheap talk' method to avoid non-commitment bias. The split sample approach has also been used to compare different experimental design approaches, such as d-optimal designs versus blocked orthogonal designs. Also encouraged are the use of experimental designs that accommodate more complete model specifications, such as error distributions around parameters, or interaction terms between choice attributes.
机译：本文讨论了前面各章中讨论的实验设计方法以及其他方法学方面的进展如何用于解决最需要改进SP技术以应对政策应用中最普遍的特定运输环境的领域。当人们可能在重复的环境中做出一系列选择时，例如在一周的不同日子上班所使用的模式时，投资组合设计可能会很有用。本文鼓励使用拆分样本方法，其中对一个随机选择的子样本使用某种实验设计变化，对其他子样本测试一种或多种其他设计方法，从而允许实验设计对待测响应的影响。此方法可用于有关受访者应如何考虑选项的不同说明，例如在“便宜的谈话”方法中，以避免非承诺偏见。分割样本方法也已用于比较不同的实验设计方法，例如d最优设计与封闭正交设计。还鼓励使用适应更完整模型规格的实验设计，例如参数周围的误差分布或选择属性之间的交互项。

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