论文标题
重新访问接收器操作特征研究的样本量规划：精确和保证的置信区间方法
Revisiting sample size planning for receiver operating characteristic studies: a confidence interval approach with precision and assurance
论文作者
论文摘要
目标：对接收器操作特征曲线（AUC）下的区域及其差异的估计是诊断研究的关键任务。我们旨在得出，评估和实施这些研究的简单样本量公式，重点是估计而不是假设检验。 材料和方法：样本量公式是通过明确纳入预先指定的精度和保证而开发的，并以置信区间的下限和保证表示实现该下限的概率表示，并表示的精度。提出了一种新的方差函数，以进行有效估计，以允许疾病和非疾病组中观察结果不平等。通过模拟评估了提出的公式的性能。 结果：获得了封闭形式的样本量公式。仿真结果表明，所提出的公式产生的经验保证概率接近预先指定的保证概率和接近名义95％的经验覆盖率。示出了现实世界中的示例供插图。 结论：根据AUC估计及其差异的样本量公式。模拟结果表明，在实现预先指定的精度和保证概率方面表现出色。用于实施该建议公式的在线计算器可在https://dishu.page/calculator/上公开获得。
Objectives: Estimation of areas under receiver operating characteristic curves (AUCs) and their differences is a key task in diagnostic studies. We aimed to derive, evaluate, and implement simple sample size formulas for such studies with a focus on estimation rather than hypothesis testing. Materials and Methods: Sample size formulas were developed by explicitly incorporating pre-specified precision and assurance, with precision denoted by the lower limit of confidence interval and assurance denoted by the probability of achieving that lower limit. A new variance function was proposed for valid estimation allowing for unequal variances of observations in the disease and non-disease groups. Performance of the proposed formulas was evaluated through simulation. Results: Closed-form sample size formulas were obtained. Simulation results demonstrated that the proposed formulas produced empirical assurance probability close to the pre-specified assurance probability and empirical coverage probability close to the nominal 95%. Real-world worked examples were presented for illustration. Conclusions: Sample size formulas based on estimation of AUCs and their differences were developed. Simulation results suggested good performance in terms of achieving pre-specified precision and assurance probability. An online calculator for implementing the proposed formulas is openly available at https://dishu.page/calculator/.
