计算机科学
意义(存在)
构造(python库)
定性研究
要素(刑法)
过程(计算)
管理科学
数据科学
数据挖掘
心理学
社会学
社会科学
操作系统
经济
程序设计语言
法学
心理治疗师
政治学
作者
Joanna Coast,Hareth Al‐Janabi,Eileen Sutton,Susan Horrocks,A. Jane Vosper,Dawn Swancutt,Terry N. Flynn
摘要
SUMMARY Attribute generation for discrete choice experiments (DCEs) is often poorly reported, and it is unclear whether this element of research is conducted rigorously. This paper explores issues associated with developing attributes for DCEs and contrasts different qualitative approaches. The paper draws on eight studies, four developed attributes for measures, and four developed attributes for more ad hoc policy questions. Issues that have become apparent through these studies include the following: the theoretical framework for random utility theory and the need for attributes that are neither too close to the latent construct nor too intrinsic to people's personality; the need to think about attribute development as a two‐stage process involving conceptual development followed by refinement of language to convey the intended meaning; and the difficulty in resolving tensions inherent in the reductiveness of condensing complex and nuanced qualitative findings into precise terms. The comparison of alternative qualitative approaches suggests that the nature of data collection will depend both on the characteristics of the question (its sensitivity, for example) and the availability of existing qualitative information. An iterative, constant comparative approach to analysis is recommended. Finally, the paper provides a series of recommendations for improving the reporting of this element of DCE studies. Copyright © 2011 John Wiley & Sons, Ltd.
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