标题： 校准数据的分析中的异常现象 显示英文标题

标题： Anomalities in the Analysis of Calibrated Data

摘要： 本研究考察了校准误差对直接校准测定法中的模型假设和数据分析工具的影响。这些影响包括：诱导的依赖性、增大的方差以及校准测量值之间的异方差性，其分布表现为混合分布。这些异常现象对传统的推论产生了不利影响，包括样本均值的一致性问题、测量方差的低估，以及样本均值、样本方差和学生t分布作为混合分布的现象。尽管均方误差继续低估测量方差，但比较实验中的推论基本保持完整。在实际应用中，这些异常现象被掩盖，因为传统的诊断方法无法识别通过校准引入的不规则性。案例研究表明了主要问题。 显示英文摘要

摘要： This study examines effects of calibration errors on model assumptions and data--analytic tools in direct calibration assays. These effects encompass induced dependencies, inflated variances, and heteroscedasticity among the calibrated measurements, whose distributions arise as mixtures. These anomalies adversely affect conventional inferences, to include the inconsistency of sample means; the underestimation of measurement variance; and the distributions of sample means, sample variances, and Student's t as mixtures. Inferences in comparative experiments remain largely intact, although error mean squares continue to underestimate the measurement variances. These anomalies are masked in practice, as conventional diagnostics cannot discern irregularities induced through calibration. Case studies illustrate the principal issues.