Stepped wedge cluster randomized trials (SWCRTs) often face challenges with potential confounding by time trends. Traditional frequentist methods can fail to provide adequate coverage of the intervention's true effect using confidence intervals, whereas Bayesian approaches show potential for better coverage of intervention effects. However, Bayesian methods have seen limited development in SWCRTs. We propose two novel Bayesian hierarchical penalized spline models for SWCRTs. The first model is for SWCRTs involving many clusters and time periods, focusing on immediate intervention effects. To evaluate its efficacy, we compared this model to traditional frequentist methods. We further developed the model to estimate time-varying intervention effects. We conducted a comparative analysis of this Bayesian spline model against an existing Bayesian monotone effect curve model. The proposed models are applied in the Primary Palliative Care for Emergency Medicine stepped wedge trial to evaluate the effectiveness of primary palliative care intervention. Extensive simulations and a real-world application demonstrate the strengths of the proposed Bayesian models. The Bayesian immediate effect model consistently achieves near the frequentist nominal coverage probability for true intervention effect, providing more reliable interval estimations than traditional frequentist models, while maintaining high estimation accuracy. The proposed Bayesian time-varying effect model exhibits advancements over the existing Bayesian monotone effect curve model in terms of improved accuracy and reliability. To the best of our knowledge, this is the first development of Bayesian hierarchical spline modeling for SWCRTs. The proposed models offer an accurate and robust analysis of intervention effects. Their application could lead to effective adjustments in intervention strategies.

翻译：阶梯楔形集群随机试验常面临时间趋势潜在混杂的挑战。传统频率学派方法在利用置信区间覆盖干预真实效应时往往效果不足，而贝叶斯方法则展现出更优的干预效应覆盖潜力。然而，贝叶斯方法在阶梯楔形集群随机试验中的发展十分有限。我们提出了两种适用于阶梯楔形集群随机试验的新型贝叶斯分层惩罚样条模型。第一种模型针对包含大量集群和时间周期的试验，聚焦于即时干预效应。为评估其效能，我们将该模型与传统频率学派方法进行了比较。我们进一步扩展了该模型以估计时变干预效应，并将此贝叶斯样条模型与现有贝叶斯单调效应曲线模型进行了对比分析。所提出的模型应用于急诊医学初级姑息治疗阶梯楔形试验，以评估初级姑息治疗干预的有效性。广泛模拟实验和真实案例分析证明了所提贝叶斯模型的优势。贝叶斯即时效应模型持续达到接近频率学派名义覆盖概率的真实干预效应置信区间，在保持高估计精度的同时，提供了比传统频率学派模型更可靠的区间估计。所提出的贝叶斯时变效应模型在准确性和可靠性方面优于现有贝叶斯单调效应曲线模型。据我们所知，这是阶梯楔形集群随机试验中贝叶斯分层样条建模的首次发展。所提模型为干预效应分析提供了精确且稳健的方案，其应用可有效调整干预策略。