有空间相关性的贝叶斯模型提高了EQ-5D-5L值集的精度
Menglu Che1, Feng Xie2, Stephanie Thomas3
1Department of Biostatistics, Yale University School of Public Health, New Haven, CT, USA.
概括
具有空间相关性的贝叶斯模型提高了EQ-5D-5L仪器的健康实用值的精度. 这些模型改善了预测,有助于医疗保健中的经济评估.
科学领域:
- 卫生经济学 卫生经济学
- 心理测量 心理测量 心理测量
- 统计建模 统计建模
背景情况:
- 来自EQ-5D-5L价值集的健康公用事业对于经济评估至关重要.
- 现有的模型可能在预测健康状态公用事业方面缺乏准确性.
研究的目的:
- 评估空间相关性建模是否能提高EQ-5D-5L值集的精度.
- 将具有空间相关性的贝叶斯模型与现有的线性和CALE模型进行比较.
主要方法:
- 利用了7项EQ-5D-5L估值研究的数据.
- 使用根平均平方误差 (RMSE) 进行外样本预测的比较预测精度.
- 对省略个人和健康状况块的评估模型.
主要成果:
- 有空间相关性的贝叶斯模型在省略单个状态时,在7个国家的线性模型上始终提高了精度.
- 在加拿大,中国,德国,印度尼西亚,日本和韩国观察到RMSE减少.
- 当省略国家块时,表现有所不同,CALE模型在4个国家表现出色.
结论:
- 有空间相关性的贝叶斯模型和CALE模型显示了提高EQ-5D-5L值设定精度的前景.
- 研究设计,包括捕获的健康状况的数量,可以进一步提高准确性.
- 建议考虑贝叶斯模型和CALE模型来制定未来的价值集.
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