Estimating Patients&Apos; Preferences for Medical Devices: Does the Number of Profile in Choice Experiments Matter?

J. Bridges, Christine Buttorff, K. Groothuis-Oudshoorn
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引用次数: 6

Abstract

Background: Most applications of choice-based conjoint analysis in health use choice tasks with two profiles, while marketing studies routinely use three or more. This study reports on a randomized trial comparing paired with triplet profile choice formats focused on hearing aids. - Methods: Respondents with hearing loss were drawn from a nationally representative cohort, completed identical surveys, and were randomized to choice tasks with two or three profiles. The primary outcomes of differences in estimated preferences were explored using t-tests, likelihood ratio tests, and analyses of individual-level models estimated with ordinary least squares. - Results: 500 respondents were recruited. 127 had no hearing loss, 28 had profound loss and 22 declined to participate and were not analyzed. Of the remaining 323 participants, 146 individuals were randomized to the pairs and 177 to triplets. Pairs and triplets produced identical rankings of attribute importance but homogeneity was rejected (P<0.0001). Pairs led to more variation, and were systematically biased toward the null because a third (32.2%) of respondents focused on only one attribute. This is in contrast to respondents in the triplet design who traded across all attributes. - Discussion: The number of profiles in choice tasks affects the results of conjoint analysis studies. Here triplets are preferred to pairs as they avoid non-trading and allow for more accurate estimation of preferences models.
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估计Patients&Apos;对医疗器械的偏好:选择实验中轮廓的数量有影响吗?
背景:大多数基于选择的联合分析在健康领域的应用都是使用两个剖面的选择任务,而市场研究通常使用三个或更多。本研究报告了一项随机试验,比较了配对和三重档案选择格式,重点是助听器。方法:听力损失的受访者从全国具有代表性的队列中抽取,完成相同的调查,并随机分配到两个或三个概况的选择任务中。使用t检验、似然比检验和用普通最小二乘估计的个人水平模型分析来探讨估计偏好差异的主要结果。-结果:招募了500名受访者。127人没有听力损失,28人听力损失严重,22人拒绝参与,未进行分析。在剩下的323名参与者中,146人被随机分为两对,177人被随机分为三胞胎。对和三胞胎产生相同的属性重要性排名,但拒绝同质性(P<0.0001)。成对导致更多的变化,并且系统地偏向于零,因为三分之一(32.2%)的受访者只关注一个属性。这与在三重设计中交易所有属性的受访者形成对比。-讨论:选择任务中剖面的数量会影响联合分析研究的结果。在这里,三胞胎比成对更受欢迎,因为它们避免了非交易,并允许对偏好模型进行更准确的估计。
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