Roy Anindya, Bhaumik Dulal K, Aryal Subhash, Gibbons Robert D
Center for Health Statistics, University of Illinois at Chicago, 1601 W. Taylor St., Chicago, Illinois 60612, USA.
Biometrics. 2007 Sep;63(3):699-707. doi: 10.1111/j.1541-0420.2007.00769.x.
We consider the problem of sample size determination for three-level mixed-effects linear regression models for the analysis of clustered longitudinal data. Three-level designs are used in many areas, but in particular, multicenter randomized longitudinal clinical trials in medical or health-related research. In this case, level 1 represents measurement occasion, level 2 represents subject, and level 3 represents center. The model we consider involves random effects of the time trends at both the subject level and the center level. In the most common case, we have two random effects (constant and a single trend), at both subject and center levels. The approach presented here is general with respect to sampling proportions, number of groups, and attrition rates over time. In addition, we also develop a cost model, as an aid in selecting the most parsimonious of several possible competing models (i.e., different combinations of centers, subjects within centers, and measurement occasions). We derive sample size requirements (i.e., power characteristics) for a test of treatment-by-time interaction(s) for designs based on either subject-level or cluster-level randomization. The general methodology is illustrated using two characteristic examples.
我们考虑用于分析聚类纵向数据的三级混合效应线性回归模型的样本量确定问题。三级设计在许多领域都有应用，尤其是在医学或健康相关研究中的多中心随机纵向临床试验。在这种情况下，第一级代表测量时间点，第二级代表个体，第三级代表中心。我们考虑的模型涉及个体水平和中心水平上时间趋势的随机效应。在最常见的情况下，个体和中心水平上都有两个随机效应（常数和单一趋势）。这里提出的方法在抽样比例、组的数量以及随时间的损耗率方面具有通用性。此外，我们还开发了一个成本模型，以帮助在几个可能相互竞争的模型（即中心、中心内个体和测量时间点的不同组合）中选择最简约的模型。我们推导了基于个体水平或聚类水平随机化的设计中治疗与时间交互作用检验的样本量要求（即功效特征）。通过两个典型例子说明了一般方法。
