Using audiometric thresholds and word recognition in a treatment study
Using audiometric thresholds and word recognition in a treatment study
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DOI：
10.1097/00129492-200601000-00020
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发表时间：
2006-01-01
影响因子：
2.1
通讯作者：
Rauch, SD
中科院分区：
文献类型：
--
作者：
Halpin, C;Rauch, SD
目的：首先，检查治疗研究中听阈改善的渐进性地板效应对显著结果的可能限制。听力恢复的地板效应表明，如果入选标准设置得不够高，可能无法检测到治疗组的优效性。第二，检查当使用两种不同类型的标准时受试者的单词识别分数的显著变化的结果。15个百分点）与95%（p = 0.05）的标准，从二项式临界差异表单音节。二项式变量的关键差异取决于起始值是否位于分数范围的中间（接近50%正确）或两端（0或100%）。不同的判断显着的单词识别的改善- ment（或减少）使用二项式与单值criteria presented.Data Source：一个最近的治疗研究突发感音神经性听力损失（n = 318）是用来说明这些effects.Conclusion：首先，有一个渐进的地板效应，提出严重程度，与结果测量听阈恢复。在某些设计中，这可能会限制检测显著差异的能力。第二，在示例数据集中，针对词识别中的受试者内显著变化（例如，15个百分点）与二项式95%关键差异表的结果相比，引入了约9%的错误分类错误率。
Objectives: First, to examine a possible limit on significant results imposed by a progressive floor effect for hearing threshold improvement in a treatment study. This floor effect for hearing recovery suggests that if inclusion criteria are not set sufficiently high, the superiority of a treatment group may not be detectable. Second, to examine the outcomes when using two different types of criteria for significant change in a subject's word recognition score.Methods: Several single-number criteria (e.g., 15 percentage points) are compared with the 95% (p = 0.05) criteria from the binomial critical difference table for monosyllables. Critical differences for binomial variables change depending on whether the starting value lies in the middle (near 50% correct) or at either extreme of the range of scores (0 or 100%). Different judgments of significant word recognition improve- ment (or decrease) using binomial versus single-value criteria are presented.Data Source: A recent treatment study of sudden sensorineural hearing loss (n = 318) is used to illustrate these effects.Conclusion: First, there is a progressive floor effect of presenting severity that covaries with the outcome measure hearing threshold recovery. In some designs, this may act to constrain the ability to detect a significant difference. Second, in the example data set, the use of single-value criteria for significant within subject change in word recognition (e.g., 15 percentage points) introduced a miscategorization error rate of approximately 9% when compared with the result of the binomial 95% critical difference table.