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The power of statistical tests using field trial count data of nontarget organisms in environmental risk assessment of genetically modified plants

机译:使用非目标生物的现场试验计数数据进行统计测试在转基因植物环境风险评估中的作用

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Publications on power analyses for field trial count data comparing transgenic and conventional crops have reported widely varying requirements for the replication needed to obtain statistical tests with adequate power. These studies are critically reviewed and complemented with a new simulation study. The reasons for the different reports are elucidated and can be classified as additional (but hidden) replication, selection of favourable endpoints with low variation, and reporting at an unusual scale. A new simulation study was performed to investigate the relationship between statistical power and replication under a variety of data-generating and analysis methods. Approximately 60 replications should be sufficient to detect a 50% (two-fold) decrease in taxon numbers, provided that the coefficient of variation in the counts does not exceed 100%. Replication can be accomplished not only by using multiple blocks in a single trial, but also by repeating the experiment in multiple years and/or at different sites. With other (e.g. agronomic) treatment factors in the field trial, without interaction with variety, the effective replication can be increased by investigating the main variety effect summed over the other treatment factors. Repeated measures may also increase the power if the expected difference is equal over time and the time points are sufficiently spaced.
机译:关于比较转基因作物和常规作物的田间试验计数数据的功效分析的出版物报道,对于获得具有足够功效的统计测试所需的复制,要求有很大不同。这些研究经过严格审查,并辅以新的模拟研究。阐明了不同报告的原因,并且可以将其归类为其他(但隐藏)复制,选择低变异性的有利终点以及以不寻常的规模进行报告。进行了一项新的模拟研究,以研究在各种数据生成和分析方法下统计能力与复制之间的关系。假设计数的变异系数不超过100%,则大约60次重复应足以检测到分类单元数量减少50%(两倍)。复制不仅可以通过在单个试验中使用多个模块来完成,而且可以通过在多年和/或不同地点重复进行该实验来完成。在田间试验中使用其他(例如农艺学)处理因子,而不会与品种相互作用,可以通过调查与其他处理因子相加的主要品种效应来提高有效复制。如果预期的差异在时间上相等并且时间点间隔足够大,则重复的措施也可能会增加功率。

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