, London, UK.
BMC Med Res Methodol. 2021 Oct 17;21(1):211. doi: 10.1186/s12874-021-01414-7.
Accuracy can be improved by taking multiple synchronous samples from each subject in a study to estimate the endpoint of interest if sample values are not highly correlated. If feasible, it is useful to assess the value of this cluster approach when planning studies. Multiple assessments may be the only method to increase power to an acceptable level if the number of subjects is limited.
The main aim is to estimate the difference in outcome between groups of subjects by taking one or more synchronous primary outcome samples or measurements. A summary statistic from multiple samples per subject will typically have a lower sampling error. The number of subjects can be balanced against the number of synchronous samples to minimize the sampling error, subject to design constraints. This approach can include estimating the optimum number of samples given the cost per subject and the cost per sample.
The accuracy improvement achieved by taking multiple samples depends on the intra-class correlation (ICC). The lower the ICC, the greater the benefit that can accrue. If the ICC is high, then a second sample will provide little additional information about the subject's true value. If the ICC is very low, adding a sample can be equivalent to adding an extra subject. Benefits of multiple samples include the ability to reduce the number of subjects in a study and increase both the power and the available alpha. If, for example, the ICC is 35%, adding a second measurement can be equivalent to adding 48% more subjects to a single measurement study.
A study's design can sometimes be improved by taking multiple synchronous samples. It is useful to evaluate this strategy as an extension of a single sample design. An Excel workbook is provided to allow researchers to explore the most appropriate number of samples to take in a given setting.
如果样本值相关性不高，则通过从研究中的每个个体中多次采集同步样本，以估计感兴趣的终点，可提高准确性。如果可行，在研究计划时评估这种聚类方法的价值是很有用的。如果研究对象数量有限，则多次评估可能是唯一一种可将效能提高到可接受水平的方法。
主要目的是通过采集一个或多个同步主要结局样本或测量值，来估计个体之间结局的差异。每个个体多个样本的汇总统计量通常具有较低的抽样误差。可以根据每个个体的成本和每个样本的成本，在设计约束下，平衡研究对象的数量和同步样本的数量，以最小化抽样误差。该方法可包括根据研究对象的成本和样本的成本，来估计给定条件下的最佳样本数量。
采集多个样本可实现的准确性提高取决于组内相关系数（ICC）。ICC 越低，可获得的收益越大。如果 ICC 较高，则第二个样本提供的关于个体真实值的附加信息很少。如果 ICC 非常低，增加一个样本等同于增加一个额外的个体。多次样本的好处包括能够减少研究中的研究对象数量，并提高效能和可用的α值。例如，如果 ICC 为 35%，则增加第二次测量相当于将单测量研究中的个体数量增加 48%。
通过采集多个同步样本，有时可以改进研究的设计。作为单次样本设计的扩展，评估这种策略是有用的。提供了一个 Excel 工作簿，允许研究人员在给定的情况下探索最合适的采样数量。
