Abstract The purpose of equivalence assessement is to recognize a significant shift between values of the same variables (elements in geochemical surveys) in two datasets. To merge two or more independent datasets that are somehow linked together to create a new integrated dataset, the significance of the difference between datasets must be determined. Merging data originated from two or more geochemical surveys can be highly beneficial to establish geochemical maps with an increased resolution and/or a covered area. Different methods of sampling, preparation and analysis are being used in various geochemical surveys which have a major impact on the measurement of the concentration of elements, and there might be a systematic shift in the concentration of the same elements. Therefore, studying the presence of a significant shift between datasets, and leveling them as a pre-processing stage is essential to combine geochemical data and provide an integrated map of a few independent surveys. While combining datasets to provide integrated maps, not assessing the equivalence and leveling the datasets leads to invalid maps. Determining the equivalence assessment between datasets is done by different methods. Quantile–Quantile Dispersion Diagram and Multiple Frequency Histogram methods have already been introduced by researchers. These methods are visual and dependent on expert judgment. In this study the Fisher test, T-student test, and Quantile–Value Diagram (QVD) are introduced to assess the equivalence between two datasets for the first time. Fisher and T-student tests are applied to compare the variance and average of the same elements in two datasets. In this study, we propose an original method for assessing the equivalence. QVD is introduced as a new method of determining the shift between multiple datasets. The case study is the equivalence assessment and shift determination between two independent geochemical surveys in north of Sarduiyeh and south of Rayen sheets (Hanza, southern part of Urmia–Dokhtar metalogenic belt, Iran). The equivalence assessment was performed for twelve elements including Zn, Pb, Ag, Ni, Bi, Cu, As, Sb, Co, W, Mo, and Mn. Based on Quantile-Quantile Dispersion Diagram and Multiple Frequency Histogram methods, some elements of the two databases were considered as equivalent, but the analysis of QVD method shows a significant shift for them. Fisher and T-student tests confirm the results of QVD. QVD is an exact method for the equivalence assessment that is not dependent on the expert judgment. Eventually, Fisher test, T-student test, and QVD are recommended simultaneously to assess the equivalence between datasets.

中文翻译：

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通过分位数-值图 (QVD) 对多个数据集进行等效评估以检测显着变化（案例研究：来自伊朗克尔曼汉扎地区的地球化学数据集）

摘要 等效性评估的目的是识别两个数据集中相同变量（地球化学调查中的元素）的值之间的显着变化。要合并两个或多个以某种方式链接在一起的独立数据集以创建新的集成数据集，必须确定数据集之间差异的重要性。合并源自两个或多个地球化学调查的数据对于建立具有更高分辨率和/或覆盖区域的地球化学图非常有益。各种地球化学调查中使用了不同的取样、制备和分析方法，对元素浓度的测量有重大影响，并且相同元素的浓度可能会发生系统性变化。因此，研究数据集之间是否存在显着转变，并将它们平整作为预处理阶段对于结合地球化学数据并提供一些独立调查的综合地图至关重要。在组合数据集以提供集成地图时，不评估等效性和平整数据集会导致地图无效。确定数据集之间的等效性评估是通过不同的方法完成的。研究人员已经引入了分位数-分位数色散图和多频直方图方法。这些方法是直观的，依赖于专家的判断。在本研究中，首次引入了 Fisher 检验、T-student 检验和分位数-值图 (QVD) 来评估两个数据集之间的等价性。Fisher 和 T-student 检验用于比较两个数据集中相同元素的方差和平均值。在这项研究中，我们提出了一种评估等效性的原始方法。QVD 被引入作为确定多个数据集之间偏移的新方法。案例研究是在 Sarduiyeh 以北和 Rayen 片以南（Hanza，Urmia-Dokhtar 成矿带南部，伊朗）的两个独立地球化学调查之间的等效评估和偏移确定。对 12 种元素进行了等效性评估，包括 Zn、Pb、Ag、Ni、Bi、Cu、As、Sb、Co、W、Mo 和 Mn。基于分位数-分位数色散图和多频直方图方法，两个数据库的某些元素被认为是等效的，但 QVD 方法的分析表明它们有显着的转变。Fisher 和 T-student 测试证实了 QVD 的结果。QVD 是一种精确的等效性评估方法，不依赖于专家判断。最终，建议同时使用 Fisher 检验、T-student 检验和 QVD 来评估数据集之间的等效性。