Equivalence testing in pesticide risk assessment -- Evaluation and practical guidance for design, analysis and interpretation
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农药风险评估中的等效性检验：设计、分析与解释
- 研究问题
- 如何设计蜜蜂田间试验，使等效性检验能可靠识别超过保护目标的农药危害，并在控制误判的同时降低所需试验成本？
- 方法与思路
- 作者用模拟比较 EFSA 原方案与基于对照组置信下界的替代检验，并考察增加地点重复、协变量调整及反聚类随机分配的效果。
- 材料陈述的贡献
- 摘要称，在所考察设计及显著性水平下，原方案更可靠地识别超标危害；增加地点数仍有必要，但调整设计可减少需求，并提供 R 函数。
- 阅读关注点
- 应核对等效性界值、两类错误与检验功效的定义，特别是显著性水平为 0.2 的解释；还需检查地点相关性及随机分配方案的模拟设定。
- 阅读边界
- 这是 arXiv 预印本，同行评审或期刊接收未经核实；结论来自模拟的蜜蜂田间设计，摘要未说明全部参数，不能直接推广到其他物种或试验。
原文摘要
Harmful pesticide effects exceeding specific protection goals (SPG) may go undetected in underpowered experimental designs. Regulatory honeybee field studies have consistently failed to reach the statistical power required under European Food Safety Authority (EFSA) guidance, which may have caused approval of high-risk substances. Therefore, EFSA advised a shift from testing the null hypothesis of 'no effect' to equivalence testing. Under this approach, a pesticide is classified as 'low risk' if the null hypothesis that its effect exceeds the SPG can be rejected. For honeybees, the recommended SPG is a colony size reduction below 10%. Critics have argued that this framework requires excessive site replication to demonstrate pesticide safety and proposed an alternative equivalence test defining treatment effects relative to the lower bound of the 90%-control-group confidence interval. Using simulations mimicking a regulatory honeybee field study, we show that although the two equivalence tests share the same trade-off between false 'low-risk' and false 'high-risk' classifications, only EFSA's original recommendation reliably identifies pesticides with effects > SPG at alpha = 0.2. Our results show that increasing site replication beyond the current practice is unavoidable for a reliable regulatory assessment. However, for pesticides with effect sizes of 5% or less, site requirements remain lower than those implied by the power requirement of the former EFSA guidance. Moreover, covariate adjustment through a model term or balanced colony allocation using anticlustering randomisation can reduce site requirements without losing power and thus save costs. Finally, we provide guidance and R functions for anticlustering randomisation and equivalence testing for pesticide risk assessment.