School of the Environment, The University of Queensland, Brisbane (Magandjin), QLD 4072, Australia.
J Exp Biol. 2024 Mar 1;227(5). doi: 10.1242/jeb.247122. Epub 2024 Mar 8.
Statistical analyses that physiologists use to test hypotheses predominantly centre on means, but the tail ends of the response distribution can behave quite differently and underpin important scientific phenomena. We demonstrate that quantile regression (QR) offers a way to bypass some limitations of least squares regression (LSR) by building a picture of independent variable effects across the whole distribution of a dependent variable. We used LSR and QR with simulated and real datasets. With simulated data, LSR showed no change in the mean response but missed significant effects in the tails of the distribution found using QR. With real data, LSR showed a significant change in the mean response but missed a lack of response in the upper quantiles which was biologically revealing. Together, this highlights that QR can help to ask and answer more questions about variation in nature.
统计分析是生理学家用来检验假设的主要方法，主要集中在平均值上，但响应分布的尾部可能表现得非常不同，并支持重要的科学现象。我们证明，分位数回归（QR）通过构建独立变量对因变量整个分布的影响图，提供了一种绕过最小二乘回归（LSR）局限性的方法。我们使用 LSR 和 QR 对模拟数据集和真实数据集进行了分析。在模拟数据中，LSR 显示平均响应没有变化，但在 QR 发现的分布尾部发现了显著的影响。在真实数据中，LSR 显示平均响应有显著变化，但错过了上四分位数的无反应，这在生物学上具有启示性。综上所述，这表明 QR 可以帮助我们提出和回答更多关于自然界变异的问题。
