从规范的休息? 在健康领域的离散选择模型中,偏好异质性的参数表示
John Buckell1, Alice Wreford2, Matthew Quaife3
1Nuffield Department of Population Health, University of Oxford, Oxford, UK.
概括
健康建模者经常在离散选择模型中使用偏好异质性的正常分布. 替代分布和模型平均值可以提高模型的合适性,并更准确地捕捉偏好分布.
科学领域:
- 健康经济学
- 经济计量学
- 行为科学
背景情况:
- 离散选择模型分析个人偏好.
- 在健康经济学中,混合逻辑模型是偏好异质性的标准.
- 目前的实践通常依赖于这些模型的正常分布.
研究的目的:
- 评估混合逻辑模型中的替代分布假设的影响.
- 将标准正常分布与其他参数规格进行比较.
- 评估模式平均化对偏好异质性的好处.
主要方法:
- 对健康中的混合逻辑模型实践进行范围审查.
- 七个替代分布的比较和模型的平均值.
- 在四个数据集中进行分析:声明偏好,显示偏好和模拟.
- 评估模型合适性,偏好分布,支付意愿和预测.
主要成果:
- 替代分布假设显著超过标准正常分布.
- 在不同模型中,偏好分布和支付预估的意愿差异很大.
- 模型的平均值提供了更大的灵活性,更好的适应性,并减轻了选择偏差.
- 分布假设没有影响模型的预测.
结论:
- 使用正常分布的标准实践对于捕捉偏好异质性是不理想的.
- 研究人员应该探索超出正常假设的替代分布.
- 模型平均是健康经济学中强有力的偏好分析的有价值方法.
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