Wilson J F, Newcombe R G, Marshall R W, Williams J, Richens A
Clin Chim Acta. 1984 Nov 30;143(3):203-16. doi: 10.1016/0009-8981(84)90070-6.
Measurements of drug concentrations from the Heathcontrol quality assessment schemes were analysed to detect the presence of intralaboratory, interlaboratory, or intermethod errors. We developed weighted least-squares regression procedures as significance tests for evaluating intralaboratory noise, curvature vs linearity, proportional errors and additive errors. The latter intercept test for additive errors was unsatisfactory and an effective alternative based on the difference between measurements and estimates of the true drug concentrations was developed. Significance of residuals was tested against the population noise, which was defined by smooth mathematical functions fitted to the standard deviation (SD) data for the drug samples. We evaluated these tests for 1,647 sets of data. Only small amounts of curvature were present, validating the linear-regression approach. Both random and proportional errors were demonstrated. The most frequent errors were additive in nature, components of which were demonstrated to be the result of intermethod differences.
对希思控制质量评估计划中的药物浓度测量值进行了分析，以检测实验室内、实验室间或方法间误差的存在。我们开发了加权最小二乘回归程序作为显著性检验，用于评估实验室内噪声、曲率与线性、比例误差和加性误差。用于加性误差的后一种截距检验并不令人满意，因此开发了一种基于测量值与真实药物浓度估计值之间差异的有效替代方法。残差的显著性是相对于总体噪声进行检验的，总体噪声由拟合药物样本标准差（SD）数据的平滑数学函数定义。我们对1647组数据评估了这些检验。仅存在少量曲率，验证了线性回归方法。随机误差和比例误差均得到证实。最常见的误差本质上是加性的，其组成部分被证明是方法间差异的结果。
