Estimation of hurst exponent for sequential monitoring of clinical trials with covariate adaptive randomization
Estimation of hurst exponent for sequential monitoring of clinical trials with covariate adaptive randomization
复制标题
协变量自适应随机化连续监测临床试验的赫斯特指数估计
DOI：
10.1016/j.cct.2022.106887
复制
发表时间：
2022
影响因子：
2.2
通讯作者：
Lai, Dejian
中科院分区：
文献类型：
--
作者：
Yang, Yiping;Zhu, Hongjian;Lai, Dejian
背景经典布朗运动（BM）已广泛应用于临床试验的监测，包括协变量自适应随机化（CAR）。在CAR设计的临床试验序贯监测过程中，通常假设独立增量性质。然而，在现实中，相关性可能存在于潜在的模型的误差项，从而导致在序贯monitoringprocess.MethodsWe依赖增量估计Hurst指数进行模拟，以评估随机属性的协变量自适应随机临床试验下两种情况：1。具有独立同分布误差项的CAR设计。2.具有相关误差项的CAR设计。研究了具有相关误差结构的协变量适应性随机临床试验的理论性质。结论在我们的研究中，证明了在CAR过程下的序贯检验统计量是渐近布朗运动，当误差结构被正确指定时。当Hurst指数等于0.5时，布朗运动是分数布朗运动的一种特殊情况。我们的模拟结果与理论上的渐近结果一致。
BackgroundClassical Brownian motion (BM) has been commonly used in monitoring clinical trials including those with covariate adaptive randomization (CAR). Independent increment property is commonly assumed in the sequential monitoring process of the clinical trials with CAR designs. However, in reality, correlation may exist in the error terms of the underlying model, resulting in dependent increment in the sequential monitoring process.MethodsWe conducted simulations for estimating the Hurst exponent to evaluate the stochastic property in the covariate adaptive randomized clinical trials under two scenarios: 1. CAR designs with independent and identically distributed error terms. 2. CAR designs with correlated error terms. The theoretical properties of covariate adaptive randomized clinical trials with correlated error structure were investigated. A test statistic including the covariance pattern of the error terms was proposed.ConclusionIn our study, the sequential test statistics under CAR procedure is shown to be asymptotically Brownian motion when the error structure is correctly specified. Further, Brownian motion is a special case of fractional Brownian motion when Hurst exponent equals to 0.5. Our simulations are consistent with the theoretical asymptotic results.