Ehrmeyer S S, Laessig R H
Clin Chem. 1987 Jun;33(6):784-7.
We developed a computer model of an interlaboratory survey program to study the ability of proficiency testing (PT) programs to detect intralaboratory errors (total, random, and systematic). It uses a base interlaboratory PT population of 400 laboratories and one test laboratory each with uniquely defined intralaboratory characteristics, i.e., mean, standard deviation (SD), and bias. A gaussian random-number generator uses these parameters to simulate 401 test results analogous to the analysis of one PT sample by each laboratory. The test laboratory's intralaboratory error is expressed as various combinations of bias and coefficient of variation (CV); its simulated survey result is evaluated by a performance criterion derived from the group statistics. To eliminate statistical artifacts, the computer model repeats the complete simulation process 400 times and determines the percentage of the test laboratory's results that fail to meet a specified performance criterion. The computer model can use assigned values or actual intralaboratory data.
我们开发了一个实验室间调查项目的计算机模型，以研究能力验证（PT）项目检测实验室内误差（总误差、随机误差和系统误差）的能力。它使用了一个由400个实验室组成的基础实验室间PT群体，以及一个每个都具有独特定义的实验室内特征（即均值、标准差（SD）和偏差）的测试实验室。一个高斯随机数生成器使用这些参数来模拟401个测试结果，类似于每个实验室对一个PT样本的分析。测试实验室的实验室内误差以偏差和变异系数（CV）的各种组合表示；其模拟调查结果通过从群体统计数据得出的性能标准进行评估。为了消除统计假象，计算机模型将完整的模拟过程重复400次，并确定测试实验室结果未达到指定性能标准的百分比。该计算机模型可以使用指定值或实际的实验室内数据。
