An experiment on simplifying conjoint analysis designs for measuring preferences.
An experiment on simplifying conjoint analysis designs for measuring preferences.
复制标题
简化测量偏好的联合分析设计的实验。
DOI：
10.1002/hec.798
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
ReedJohnson,F
中科院分区：
文献类型：
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作者：
Maddala,Tara;Phillips,KathrynA;ReedJohnson,F
在联合分析（CA）研究中，在具有多个健康属性的情景之间进行选择可能对受访者要求很高。本研究考察了通过使用具有更多属性水平重叠的设计来简化CA设计中的选择任务是否优于标准最小重叠方法。两种实验条件，最小和增加重叠离散选择CA设计，作为更大的HIV检测偏好调查的一部分，对353名受访者进行了管理。在最小重叠调查中，所有六个属性水平都允许变化。在增加重叠调查中，每组情景之间平均有两个属性水平相同。我们假设增加重叠设计将减少认知负担，同时对统计效率的影响最小。我们没有发现在一致性，交易意愿，感知困难，疲劳或效率方面有任何显着改善，尽管有几个结果是在预期的方向。然而，有证据表明，在陈述的偏好方面存在差异。结果增加了我们对受访者如何回答CA问题以及如何改进未来调查的理解。版权所有© 2003年约翰威利父子有限公司。
In conjoint analysis (CA) studies, choosing between scenarios with multiple health attributes may be demanding for respondents. This study examined whether simplifying the choice task in CA designs, by using a design with more overlap of attribute levels, provides advantages over standard minimal‐overlap methods. Two experimental conditions, minimal and increased‐overlap discrete choice CA designs, were administered to 353 respondents as part of a larger HIV testing preference survey. In the minimal‐overlap survey, all six attribute levels were allowed to vary. In the increased‐overlap survey, an average of two attribute levels were the same between each set of scenarios. We hypothesized that the increased‐overlap design would reduce cognitive burden, while minimally impacting statistical efficiency. We did not find any significant improvement in consistency, willingness to trade, perceived difficulty, fatigue, or efficiency, although several results were in the expected direction. However, evidence suggested that there were differences in stated preferences. The results increase our understanding of how respondents answer CA questions and how to improve future surveys. Copyright © 2003 John Wiley & Sons, Ltd.