AI 中文总结
研究多干预阶梯楔形设计临床试验中参数时变治疗效果，开发统一框架将参数暴露-反应函数纳入设计矩阵，推导相关GLS表达式，揭示时变效应影响，表明估计量依赖假设，不考虑会致功效校准错误和推断偏差。
AI 中文摘要
阶梯楔形设计（SWD）试验通常假设治疗效果在实施后立即显现，但在实际应用中，效果随暴露时间演变，这一假设往往不现实。在多干预阶梯楔形设计（M-SWD）中，由于其复杂的交叉模式，这种影响更加复杂。现有工作在分析阶段使用非参数方法处理主效应的时变治疗效果；然而，M-SWD中设计阶段的功效和估计量解释的影响在很大程度上仍未得到解决。我们开发了一个统一框架，将参数暴露-反应函数纳入修改后的固定效应设计矩阵Z*，并推导了模型错误设定下治疗效果估计量、方差、功效和偏差的相应广义最小二乘（GLS）表达式。分析和模拟结果表明，时变效应可能需要将达到名义目标功效所需的聚类数量增加数倍。错误设定还可能在治疗效果估计中引起大偏差，对交互效应有特别明显和不均匀的影响。这些发现表明，M-SWD中的治疗效果估计量严重依赖于关于暴露时间动态的假设，未能考虑时变效应可能导致功效的严重错误校准和有偏差的推断，对主效应和交互效应的影响不同。
英文摘要
Stepped wedge design (SWD) trials typically assume that treatment effects are immediate following implementation, but this assumption is often unrealistic in pragmatic settings where effects evolve over exposure time. This impact is further complicated in multiple-intervention stepped wedge designs (M-SWDs), due to their complex crossover patterns. Existing work has addressed time-varying treatment effects for main effects at the analysis stage using nonparametric approaches; however, the implications for design-stage power and estimand interpretation in M-SWDs remain largely unaddressed. We develop a unified framework that incorporates parametric exposure-response functions into a modified fixed-effects design matrix, Z*, and derive corresponding generalized least squares (GLS) expressions for treatment effect estimands, variance, power, and bias under model misspecification. Analytic and simulation results demonstrate that time-varying effects can require multiple-fold increase in the number of clusters required to achieve the nominal target power. Misspecification can also induce large bias in treatment effect estimates, with particularly pronounced and non-uniform impacts on interaction effects. These findings demonstrate that treatment effect estimands in M-SWDs depend critically on assumptions about exposure-time dynamics and that failure to account for time-varying effects can lead to substantial miscalibration of power and biased inference, affecting main and interaction effects differently.
Comments39 pages, 26 figures
