Marcus A H, Elias R W
National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.
Environ Health Perspect. 1998 Dec;106 Suppl 6(Suppl 6):1541-50. doi: 10.1289/ehp.98106s61541.
Although formal hypothesis tests provide a convenient framework for displaying the statistical results of empirical comparisons, standard tests should not be used without consideration of underlying measurement error structure. As part of the validation process, predictions of individual blood lead concentrations from models with site-specific input parameters are often compared with blood lead concentrations measured in field studies that also report lead concentrations in environmental media (soil, dust, water, paint) as surrogates for exposure. Measurements of these environmental media are subject to several sources of variability, including temporal and spatial sampling, sample preparation and chemical analysis, and data entry or recording. Adjustments for measurement error must be made before statistical tests can be used to empirically compare environmental data with model predictions. This report illustrates the effect of measurement error correction using a real dataset of child blood lead concentrations for an undisclosed midwestern community. We illustrate both the apparent failure of some standard regression tests and the success of adjustment of such tests for measurement error using the SIMEX (simulation-extrapolation) procedure. This procedure adds simulated measurement error to model predictions and then subtracts the total measurement error, analogous to the method of standard additions used by analytical chemists.
虽然形式化的假设检验为展示实证比较的统计结果提供了便利的框架，但在未考虑潜在测量误差结构的情况下不应使用标准检验。作为验证过程的一部分，根据具有特定场地输入参数的模型对个体血铅浓度的预测，通常会与现场研究中测得的血铅浓度进行比较，这些现场研究还报告了环境介质（土壤、灰尘、水、油漆）中的铅浓度作为暴露的替代指标。这些环境介质的测量存在多种变异性来源，包括时间和空间采样、样品制备和化学分析，以及数据录入或记录。在使用统计检验对环境数据与模型预测进行实证比较之前，必须对测量误差进行调整。本报告使用一个未公开的中西部社区儿童血铅浓度真实数据集，说明了测量误差校正的效果。我们展示了一些标准回归检验明显失效的情况，以及使用SIMEX（模拟外推）程序对这类检验进行测量误差调整的成功案例。该程序将模拟测量误差添加到模型预测中，然后减去总测量误差，这类似于分析化学家使用的标准加入法。
