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模拟患者对全科医生预约属性的偏好异质性。

Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment.

作者信息

Hole Arne Risa

机构信息

National Primary Care Research and Development Centre, Centre for Health Economics, Alcuin 'A' Block, University of York, York YO10 5DD, UK.

出版信息

J Health Econ. 2008 Jul;27(4):1078-1094. doi: 10.1016/j.jhealeco.2007.11.006. Epub 2007 Nov 29.

Abstract

This paper examines the distribution of preferences among respondents to a discrete choice experiment on the choice of general practitioner appointments. In addition to standard logit, mixed and latent class logit models are used to analyse the data from the choice experiment. It is found that there is significant preference heterogeneity for all the attributes in the experiment and that both the mixed and latent class models lead to significant improvements in fit compared to the standard logit model. Moreover, the distribution of preferences implied by the preferred mixed and latent class models is similar for many attributes.

摘要

本文研究了关于全科医生预约选择的离散选择实验中受访者的偏好分布。除了标准逻辑回归模型外,还使用混合逻辑回归模型和潜在类别逻辑回归模型来分析来自选择实验的数据。研究发现,实验中所有属性都存在显著的偏好异质性,并且与标准逻辑回归模型相比,混合逻辑回归模型和潜在类别逻辑回归模型在拟合度上都有显著提高。此外,首选的混合逻辑回归模型和潜在类别逻辑回归模型所隐含的偏好分布在许多属性上是相似的。

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