Department of Clinical Sciences, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9066, United States.
Contemp Clin Trials. 2012 May;33(3):550-6. doi: 10.1016/j.cct.2012.02.004.
Sample size calculations based on two-sample comparisons of slopes in repeated measurements have been reported by many investigators. In contrast, the literature has paid relatively little attention to the sample size calculations for time-averaged differences in the presence of missing data in repeated measurement studies. Diggle et al. (2002) provided a sample size formula detecting time-averaged differences for continuous outcomes in repeated measurement studies assuming no missing data and the compound symmetry (CS) correlation structure among outcomes from the same subject. In this paper we extend Diggle et al.'s timeaveraged difference sample size formula by allowing missing data and various correlation structures. We propose to use the generalized estimating equation (GEE) method to compare the time-averaged differences in repeatedmeasurement studies and introduce a closed form formula for sample size and power. Simulation studies were conducted to investigate the performance of GEE sample size formula with small sample sizes, a damped exponential family of correlation structures and missing data. The proposed sample size formula is illustrated using a clinical trial example.
许多研究人员已经报道了基于重复测量中斜率的两样本比较的样本量计算。相比之下，文献中对重复测量研究中存在缺失数据时时间平均差异的样本量计算相对关注较少。Diggle 等人（2002 年）提供了一个样本量公式，用于检测重复测量研究中连续结果的时间平均差异，假设没有缺失数据并且同一受试者的结果具有复合对称（CS）相关性结构。在本文中，我们通过允许缺失数据和各种相关结构来扩展 Diggle 等人的时间平均差异样本量公式。我们建议使用广义估计方程（GEE）方法来比较重复测量研究中的时间平均差异，并引入一个用于样本量和功效的闭式公式。模拟研究用于研究小样本量、阻尼指数家族相关性结构和缺失数据下 GEE 样本量公式的性能。使用临床试验示例说明了建议的样本量公式。
