Investigation of suspect surface contamination in a building may require comparative sampling across different zones to provide meaningful information with regard to contaminant sources, pathways and/or extent of dispersal. However, evaluation of the data using traditional null hypothesis significance testing (NHST) based upon the mean may result in misleading inference when encountering erratic distributions typical of environmental contaminant data. Sampling data (n = 90) for lead content in surface dust collected throughout a historic building with suspect contamination from uncontrolled disturbance to lead coatings were evaluated using traditional NHST and randomization/permutation inference; the latter metric was the maximum difference in frequency of detection (Δfd _max), to directly calculate the probability of the observed differences. In the examples for lead in surface dust presented herein, areas with “lower” mean concentration and/or no significant difference via NHST actually represented “greater contamination,” as Δfd _max indicated a greater probability of encountering lead at higher concentrations. Resulting conclusions with regard to sources and pathways contradicted those generated from traditional NHST, and underscore the need to recognize differences in applicability of different inference approaches, depending upon the distribution of the data and the particular problem. This is particularly relevant for forensic purposes.

Implications

The use of permutation/randomization inference to gain insight into sources and pathways of contamination may be more appropriate than the conventional Neyman/Pearson (N/P) logic in negative hypothesis significance testing (NHST). This suggests a broader understanding by environmental professionals of the assumptions and limitations of NHST and alternative inference such as through permutation/randomization is warranted.

中文翻译：

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评估历史建筑中的背景微粒污染-表面铅负载和污染。

对建筑物中可疑表面污染的调查可能需要跨不同区域进行比较采样，以提供有关污染物来源，途径和/或扩散程度的有意义的信息。但是，使用传统的基于假设的零假设假设显着性检验（NHST）评估数据可能会导致遇到环境污染物数据典型的不稳定分布时产生误导性推断。使用传统的NHST和随机/置换推论评估了整个历史建筑中表面灰尘中铅含量的采样数据（n = 90），其中怀疑污染物是由不受控制的干扰导致的铅涂层污染。后者度量是在检测的频率（最大差值Δfd_最大），直接计算观察到的差异的概率。在用于引线的实施例在表面的尘埃本文中所呈现，具有“降低”平均浓度和/或经由无NHST差异显著实际上表示“大于污染”，如Δfd区域_最大显示在较高浓度下遇到引线的概率更大。关于来源和途径的最终结论与传统NHST产生的结论相矛盾，并强调需要根据数据的分布和特定问题来认识不同推断方法的适用性差异。这对于法医目的尤其重要。

含义

在否定性假设显着性检验（NHST）中，使用排列/随机推理来了解污染的来源和途径可能比常规的Neyman / Pearson（N / P）逻辑更合适。这表明环境专业人士对NHST的假设和局限性有了更广泛的了解，并且有必要通过诸如置换/随机化等替代推理。