Several methods to investigate relative attribute impact in stated preference experiments
Several methods to investigate relative attribute impact in stated preference experiments
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DOI：
10.1016/j.socscimed.2006.12.007
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发表时间：
2007-04-01
影响因子：
5.4
通讯作者：
Flynn, Terry
中科院分区：
文献类型：
--
作者：
Lancsar, Emily;Louviere, Jordan;Flynn, Terry
越来越多的人使用离散选择实验（DCE）来研究人们对产品和项目的偏好，以及对构成这些产品和项目的属性的偏好。然而，在许多选择实验的解释中忽视的一个根本问题是，根据VCE响应数据估计的属性参数与公用事业的潜在主观尺度相混淆，严格来说，不能解释为相对“权重”或“影响”属性，就像健康经济学文献中经常做的那样。因此，不能使用属性参数大小和重要性来比较相对属性影响。相反，为了调查每个属性的相对影响，需要可比较的测量单位;也就是说，一个共同的、可比较的尺度。我们提出并实证证明了五种方法，允许这样的比较菜单：（1）部分对数似然分析;（2）非线性模型的边际替代率;（3）希克斯福利措施;（4）概率分析;（5）最佳-最差属性缩放。我们讨论了每种方法的优点和缺点，并提出了每种方法都适用的情况。(c)2006爱思唯尔有限公司保留所有权利。
There is growing use of discrete choice experiments (DCEs) to investigate preferences for products and programs and for the attributes that make up such products and programs. However, a fundamental issue overlooked in the interpretation of many choice experiments is that attribute parameters estimated from DCE response data are confounded with the underlying subjective scale of the utilities, and strictly speaking cannot be interpreted as the relative "weight" or "impact" of the attributes, as is frequently done in the health economics literature. As such, relative attribute impact cannot be compared using attribute parameter size and significance. Instead, to investigate the relative impact of each attribute requires commensurable measurement units; that is, a common, comparable scale. We present and demonstrate empirically a menu of five methods that allow such comparisons: (1) partial log-likelihood analysis; (2) the marginal rate of substitution for non-linear models; (3) Hicksian welfare measures; (4) probability analysis; and (5) best-worst attribute scaling. We discuss the advantages and disadvantages of each method and suggest circumstances in which each is appropriate. (c) 2006 Elsevier Ltd. All rights reserved.