论文标题
群集随机试验的样本量计算，其膨胀计数结果
Sample Size Calculation for Cluster Randomized Trials with Zero-inflated Count Outcomes
论文作者
论文摘要
群集随机步道（CRT）已广泛用于医学和公共卫生研究。许多临床计数结果，例如疗养院中的跌倒数量，表现出零值。在零通货膨胀的情况下，基于泊松或负二项式分布的计数数据的传统功率分析方法可能不足。在这项研究中，我们提出了一种用于零充气计数结果的CRT的样本量方法。它是基于GEE回归而开发的，直接对拉链结局的边际平均值进行建模，从而避免了在传统建模方法下测试两种干预效应的挑战。得出了一个封闭形式的样本量公式，该公式适当地说明了零通货膨胀，ICC由于聚类，不平衡的随机化以及集群尺寸的可变性。强大的方法，包括基于T分布的近似值和折刀重采样方差估算器，用于增强在小样本量下的试验性能。进行了广泛的模拟以评估所提出方法的性能。应用示例在实际的临床试验环境中介绍。
Cluster randomized trails (CRT) have been widely employed in medical and public health research. Many clinical count outcomes, such as the number of falls in nursing homes, exhibit excessive zero values. In the presence of zero inflation, traditional power analysis methods for count data based on Poisson or negative binomial distribution may be inadequate. In this study, we present a sample size method for CRTs with zero-inflated count outcomes. It is developed based on GEE regression directly modeling the marginal mean of a ZIP outcome, which avoids the challenge of testing two intervention effects under traditional modeling approaches. A closed-form sample size formula is derived which properly accounts for zero inflation, ICCs due to clustering, unbalanced randomization, and variability in cluster size. Robust approaches, including t-distribution-based approximation and Jackknife re-sampling variance estimator, are employed to enhance trial properties under small sample sizes. Extensive simulations are conducted to evaluate the performance of the proposed method. An application example is presented in a real clinical trial setting.
