Suppr超能文献

考虑到右截断的计数结局的群组随机试验的样本量和功效。

Sample size and power considerations for cluster randomized trials with count outcomes subject to right truncation.

机构信息

Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.

Center for Methods in Implementation and Prevention Science, Yale University, New Haven, CT, USA.

出版信息

Biom J. 2021 Jun;63(5):1052-1071. doi: 10.1002/bimj.202000230. Epub 2021 Mar 10.

Abstract

Cluster randomized trials (CRTs) are widely used in epidemiological and public health studies assessing population-level effect of group-based interventions. One important application of CRTs is the control of vector-borne disease, such as malaria. However, a particular challenge for designing these trials is that the primary outcome involves counts of episodes that are subject to right truncation. While sample size formulas have been developed for CRTs with clustered counts, they are not directly applicable when the counts are right truncated. To address this limitation, we discuss two marginal modeling approaches for the analysis of CRTs with truncated counts and develop two corresponding closed-form sample size formulas to facilitate the design of such trials. The proposed sample size formulas allow investigators to explore the power under a large number of scenarios without computationally intensive simulations. The proposed formulas are validated in extensive simulations. We further explore the implication of right truncation on power and apply the proposed formulas to illustrate the power calculation for a malaria control CRT where the primary outcome is subject to right truncation.

摘要

集群随机试验(CRTs)广泛应用于评估基于群体干预的人群水平效果的流行病学和公共卫生研究中。CRTs 的一个重要应用是控制虫媒疾病,例如疟疾。然而,设计这些试验的一个特殊挑战是,主要结局涉及到受右截断的发作次数的计数。虽然已经为具有聚类计数的 CRTs 开发了样本量公式,但当计数受到右截断时,它们并不直接适用。为了解决这个限制,我们讨论了两种用于分析截断计数 CRT 的边缘建模方法,并开发了两个相应的闭式样本量公式,以方便此类试验的设计。所提出的样本量公式允许研究人员在不进行计算密集型模拟的情况下探索大量场景下的功效。所提出的公式在广泛的模拟中得到了验证。我们进一步探讨了右截断对功效的影响,并应用所提出的公式来说明主要结局受到右截断的疟疾控制 CRT 的功效计算。

相似文献

引用本文的文献

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验