Murray D M, Hannan P J, Wolfinger R D, Baker W L, Dwyer J H
Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis 55454, USA.
Stat Med. 1998 Jul 30;17(14):1581-600. doi: 10.1002/(sici)1097-0258(19980730)17:14<1581::aid-sim864>3.0.co;2-n.
This study used Monte Carlo simulations to evaluate the performance of alternative models for the analysis of group-randomized trials having more than two time intervals for data collection. The major distinction among the models tested was the sampling variance of the intervention effect. In the mixed-model ANOVA, the sampling variance of the intervention effect is based on the variance among group x time-interval means. In the random coefficients model, the sampling variance of the intervention effect is based on the variance among the group-specific slopes. These models are equivalent when the design includes only two time intervals, but not when there are more than two time intervals. The results indicate that the mixed-model ANOVA yields unbiased estimates of sampling variation and nominal type I error rates when the group-specific time trends are homogenous. However, when the group-specific time trends are heterogeneous, the mixed-model ANOVA yields downwardly biased estimates of sampling variance and inflated type I error rates. In contrast, the random coefficients model yields unbiased estimates of sampling variance and the nominal type I error rate regardless of the pattern among the groups. We discuss implications for the analysis of group-randomized trials with more than two time intervals.
本研究采用蒙特卡罗模拟来评估用于分析具有两个以上数据收集时间间隔的群组随机试验的替代模型的性能。所测试模型之间的主要区别在于干预效应的抽样方差。在混合模型方差分析中，干预效应的抽样方差基于组×时间间隔均值之间的方差。在随机系数模型中，干预效应的抽样方差基于特定组斜率之间的方差。当设计仅包括两个时间间隔时，这些模型是等效的，但当时间间隔超过两个时则不然。结果表明，当特定组的时间趋势相同时，混合模型方差分析会产生抽样变异和名义I型错误率的无偏估计。然而，当特定组的时间趋势不同时，混合模型方差分析会产生抽样方差的向下偏差估计和膨胀的I型错误率。相比之下，无论组间模式如何，随机系数模型都会产生抽样方差和名义I型错误率的无偏估计。我们讨论了对具有两个以上时间间隔的群组随机试验分析的影响。
