N-of-1试验是在单个个体中进行的多周期交叉试验，其主要目标是估计治疗效果对个体的影响，而不是人群水平的平均反应。与常规的交叉试验一样，在N-of-1试验中理解治疗的迁移效应非常重要，特别是当没有间隔期来减少试验持续时间时。为了解决在研究期间进行大量测量时这个问题，我们引入了一种新的贝叶斯分布滞后模型，可以便于估计迁移效应，同时使用自回归模型考虑时间相关性。具体而言，我们对滞后系数提出了先验方差协方差结构，以解决治疗暴露通常在连续几天上是相同的这一事实引起的共线性问题。注意到所提出的贝叶斯模型和惩罚回归之间的联系。仿真结果表明，与其他现有方法相比，所提出的模型在估计迁移效应和立即效应时显著降低了均方根误差，而在估计总效应时则相当可比。我们还应用所提出的方法来评估光疗对缓解癌症幸存者抑郁症状的迁移效应程度。© 2023 John Wiley & Sons Ltd.

An N-of-1 trial is a multi-period crossover trial performed in a single individual, with a primary goal to estimate treatment effect on the individual instead of population-level mean responses. As in a conventional crossover trial, it is critical to understand carryover effects of the treatment in an N-of-1 trial, especially when no washout periods between treatment periods are instituted to reduce trial duration. To deal with this issue in situations where a high volume of measurements are made during the study, we introduce a novel Bayesian distributed lag model that facilitates the estimation of carryover effects, while accounting for temporal correlations using an autoregressive model. Specifically, we propose a prior variance-covariance structure on the lag coefficients to address collinearity caused by the fact that treatment exposures are typically identical on successive days. A connection between the proposed Bayesian model and penalized regression is noted. Simulation results demonstrate that the proposed model substantially reduces the root mean squared error in the estimation of carryover effects and immediate effects when compared to other existing methods, while being comparable in the estimation of the total effects. We also apply the proposed method to assess the extent of carryover effects of light therapies in relieving depressive symptoms in cancer survivors.© 2023 John Wiley & Sons Ltd.