Evaluation of Statistical Treatments of Left-Censored Environmental Data Using Coincident Uncensored Data Sets. II. Group Comparisons
Evaluation of Statistical Treatments of Left-Censored Environmental Data Using Coincident Uncensored Data Sets. II. Group Comparisons
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DOI：
10.1021/acs.est.5b02385
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发表时间：
2015-11-17
影响因子：
11.4
通讯作者：
Antweiler, Ronald C.
中科院分区：
文献类型：
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作者：
Antweiler, Ronald C.
用于确定两组删失环境数据是否来自同一分布的统计处理的主要类别是替代方法、最大似然(MLE)技术和非参数方法。这些处理连同使用所有仪器生成的数据(IN)，甚至那些低于检测下限的数据，都是通过检查550个数据集进行评估的，在这些数据集中，审查数据的真值是已知的，因此可以计算出“真”概率，并将其用作比较的标尺。研究发现，技术“质量”强烈依赖于群体中存在的审查程度。对于低审查程度(40%审查)，没有任何技术能提供真实概率的可靠估计。群体规模似乎不会影响结果的质量，而且相对于群体规模，似乎没有任何技术比其他技术变得更好或更差。最后，与其他技术相比，IN似乎做得很好，无论是审查还是组大小。
The main classes of statistical treatments that have been used to determine if two groups of censored environmental data arise from the same distribution are substitution methods, maximum likelihood (MLE) techniques, and nonparametric methods. These treatments along with using all instrument-generated data (IN), even those less than the detection limit, were evaluated by examining 550 data sets in which the true values of the censored data were known, and therefore "true" probabilities could be calculated and used as a yardstick for comparison. It was found that technique "quality" was strongly dependent on the degree of censoring present in the groups. For low degrees of censoring (40% censoring), no technique provided reliable estimates of the true probability. Group size did not appear to influence the quality of the result, and no technique appeared to become better or worse than other techniques relative to group size. Finally, IN appeared to do very well relative to the other techniques regardless of censoring or group size.