Department of Applied Mathematics, Chung Yuan Christian University, Taoyuan, Taiwan, 32023, Republic of China.
Department of Management Science, National Chiao Tung University, Hsinchu, Taiwan, 30010, Republic of China.
BMC Med Res Methodol. 2019 Mar 12;19(1):54. doi: 10.1186/s12874-019-0697-9.
Linear regression analysis is a widely used statistical technique in practical applications. For planning and appraising validation studies of simple linear regression, an approximate sample size formula has been proposed for the joint test of intercept and slope coefficients.
The purpose of this article is to reveal the potential drawback of the existing approximation and to provide an alternative and exact solution of power and sample size calculations for model validation in linear regression analysis.
A fetal weight example is included to illustrate the underlying discrepancy between the exact and approximate methods. Moreover, extensive numerical assessments were conducted to examine the relative performance of the two distinct procedures.
The results show that the exact approach has a distinct advantage over the current method with greater accuracy and high robustness.
线性回归分析是实际应用中广泛使用的统计技术。对于简单线性回归的规划和评估验证研究，已经提出了一种用于截距和斜率系数联合检验的近似样本量公式。
本文的目的是揭示现有近似方法的潜在缺陷，并为线性回归分析中模型验证的功效和样本量计算提供替代和精确的解决方案。
包含一个胎儿体重的例子来说明精确方法和近似方法之间的潜在差异。此外，还进行了广泛的数值评估，以检查两种不同方法的相对性能。
结果表明，与当前方法相比，精确方法具有明显的优势，具有更高的准确性和高稳健性。
