Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA.
Contemp Clin Trials. 2009 Mar;30(2):141-9. doi: 10.1016/j.cct.2008.11.003. Epub 2008 Nov 18.
A recent pilot crossover study of deep brain stimulation for Tourette syndrome involved the counting of motor and sonic tics from video recordings of patients. The evaluation of a five-minute video (divided into ten 30-second segments) in each of eight intervention states per patient was found to be very tedious and time-consuming. The present study sought to determine the statistical implications of reducing this data collection burden. To make maximal use of data from the small sample (n=5) pilot study, we fit linear mixed effects models to the tic count data. As suggested by an empirical examination of within-person correlations, a novel random effects covariance structure, which we refer to as a 'partitioned random effects model' was found to provide the best fit to the data. The best model for each tic type was then used to estimate relative efficiencies for specified data reductions. This analysis indicated that using a subset of five out of 10 segments would require only a 10% increase in sample size to maintain a specified power. Lastly, the bias of estimated treatment effects based on the reduced data collection was evaluated, and the particular five-segment subsets with the smallest estimated bias were determined.
最近一项关于深部脑刺激治疗抽动秽语综合征的先导性交叉研究涉及对患者视频记录中的运动性抽搐和发声性抽搐进行计数。评估每位患者的八个干预状态下的五分钟视频（分为十个 30 秒的片段）非常繁琐且耗时。本研究旨在确定减少这种数据收集负担的统计意义。为了充分利用小样本（n=5）先导研究的数据，我们对抽搐计数数据拟合了线性混合效应模型。根据对个体内相关性的实证检验，我们发现一种新颖的随机效应协方差结构，即“分区随机效应模型”，为数据提供了最佳拟合。然后，我们使用每种抽搐类型的最佳模型来估计指定数据减少的相对效率。这项分析表明，使用 10 个片段中的 5 个子集仅需将样本量增加 10%，即可保持指定的功效。最后，评估了基于减少数据收集的治疗效果估计的偏差，并确定了具有最小估计偏差的特定五个片段子集。
