Foster T A, Asztalos B F
Department of Biostatistics, School of Public Health and Tropical Medicine, Tulane University Medical Center, New Orleans, LA 70112, USA.
Clin Chim Acta. 2001 Dec;314(1-2):55-66. doi: 10.1016/s0009-8981(01)00630-1.
When developing a new laboratory test for study of human diseases, it is important to identify and control internal and external sources of variation that affect test results. It is also imperative that the precision of the test not only meets pre-established requirements and not exceed allowable total error, but also that these objectives are reached without undue expenditure of either time or financial resources.
This study applies statistical principles in designing a cost-effective experimental approach for determining the analytical precision of a new test. This approach applies the statistical concept of variance components to the problem of balancing a pre-established level of analytical precision against expenses incurred in achieving this precision.
We demonstrated (1) estimation of variance components, (2) use of these estimates for improving allocation of costs within the experiment, and (3) use of these estimates for determining the optimal number of replicate measurements.
Although elimination of all sources of variation that can affect laboratory test results is unlikely, the application of analysis of variance (ANOVA) statistical techniques can lead to a cost-effective allocation of resources for estimating the precision of a laboratory test.
在开发用于人类疾病研究的新实验室检测方法时，识别并控制影响检测结果的内部和外部变异来源非常重要。同样至关重要的是，检测的精密度不仅要满足预先设定的要求且不超过允许的总误差，而且要在不花费过多时间或财力的情况下实现这些目标。
本研究运用统计学原理设计一种经济高效的实验方法来确定新检测方法的分析精密度。该方法将方差分量的统计概念应用于平衡预先设定的分析精密度水平与实现该精密度所产生的费用这一问题。
我们展示了（1）方差分量的估计，（2）利用这些估计来改进实验中的成本分配，以及（3）利用这些估计来确定重复测量的最佳次数。
尽管消除所有可能影响实验室检测结果的变异来源不太可能，但应用方差分析（ANOVA）统计技术可以实现资源的经济高效分配，以估计实验室检测的精密度。
