离散选择实验:关于构建D-最佳和近最佳选择集的概述
Abdulrahman S Alamri1,2, Stelios Georgiou1, Stella Stylianou1
1School of Science, Royal Melbourne Institute of Technology University, Melbourne, VIC, 3000, Australia.
Heliyon
|August 4, 2023
概括
本研究比较了离散选择实验 (DCE) 设计方法,以尽量减少有效调查的选择集. 结果引导研究人员确定最佳样本大小,以便有效的实验设计.
科学领域:
- 行为经济学是一种行为经济学.
- 实验设计 实验设计
- 调查方法 调查方法
背景情况:
- 离散选择实验 (DCE) 对于估计和预测个人选择行为使用声明偏好数据至关重要.
- 有效的DCE依赖于精心构建的实验设计,通常涉及有限数量的选择集和每个集的替代方案,以提高响应效率.
- 虽然算法 (高效) 设计是常见的,但最佳 (直角) 设计仍在使用,特别是当以前的人口偏好信息无法获得时.
研究的目的:
- 为仅关注主要效应的模型提供文献中离散选择实验构建方法的概述.
- 为了比较各种最佳和近最佳的设计施工技术,基于它们在尽量减少选择集数量的效率.
- 解决从业人员对不同设计技术在实现高效率与最小的选择集的性能方面的担忧.
主要方法:
- 进行了一项文献审查,以识别和分类离散选择实验设计的不同构造方法.
- 进行了对各种最佳和近最佳设计施工方法的比较分析.
- 进行比较的主要指标是每个方法能够将调查所需的选择集数量最小化的能力.
主要成果:
- 这项研究审查和比较了构建离散选择实验设计的不同技术,重点关注只有主要效应的模型.
- 该比较评估了各种施工方法在减少选择套件数量的有效性,同时保持高设计效率.
- 关键发现突出了不同设计策略之间关于选择集数量和整体实验效率的权衡.
结论:
- 该研究提供了对各种离散选择实验设计施工方法性能的见解.
- 结果揭示了在这个领域进行高效实验所需的最佳样本大小.
- 这项工作旨在通过了解不同设计方法的优势,帮助研究人员设计更有效的离散选择实验.
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