在离散选择实验中探索启发式并评估其影响:一个原则证明
Stella M Marceta1, Nicholas V R Smeele1, Joffre D Swait1
1Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, Netherlands; Erasmus Choice Modelling Centre, Erasmus University Rotterdam, Rotterdam, Netherlands; Erasmus Centre for Health Economics Rotterdam, Erasmus University Rotterdam, Rotterdam, Netherlands.
Social science & medicine (1982)
|February 10, 2026
概括
离散选择实验 (DCE) 由于受访者启发式,经常违反随机效用理论 (RUT) 的假设. 考虑这些启发式计算可以提高偏好估计和健康研究中吸收预测的准确性.
科学领域:
- 卫生经济学 卫生经济学
- 行为经济学是一种行为经济学.
- 决策科学科学 决策科学
背景情况:
- 离散选择实验 (DCE) 被广泛用于医疗保健中的偏好模型.
- 传统上,DCE假定基于随机效用理论 (RUT) 的理性决策.
- 现实世界的健康选择可能是复杂的,导致基于启发式的决策,这违反了RUT.
研究的目的:
- 展示在DCE研究中识别和评估违反RUT的启发式方法的影响的方法.
- 为在健康偏好研究中建模基于启发式行为提供指导.
主要方法:
- 利用三个现有的DCE研究来说明启发式影响评估.
- 开发了一个结构化的面试指南和评分工具,由临床医生和研究人员的输入提供信息,以确定启发式.
- 使用带有限制参数的隐性类模型来估计启发式效应以及偏好异质性.
主要成果:
- 敏感性分析表明,高达22%的受访者可能使用了特定的启发式.
- 忽视启发式分析导致偏见的偏好估计;例如,考虑占主导地位的决策使低抗生素耐药性治疗的支付意愿增加了15.63.3欧元.
- 启发式学习显著影响了边际替代率和预测的吸收率.
结论:
- 在DCE中未能考虑违反RUT的启发式分析,从而影响了关键偏好指标和预测.
- 研究人员应将启发式评估纳入DCE研究的灵敏度分析.
- 这种方法提高了健康偏好研究结果的稳定性和准确性.
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