Stinchcombe John R, Agrawal Aneil F, Hohenlohe Paul A, Arnold Stevan J, Blows Mark W
Department of Ecology & Evolutionary Biology, and Centre for the Analysis of Genome Evolution & Function, University of Toronto, Toronto, ON M5S 3B2, Canada.
Evolution. 2008 Sep;62(9):2435-40. doi: 10.1111/j.1558-5646.2008.00449.x. Epub 2008 Jul 4.
The use of regression analysis has been instrumental in allowing evolutionary biologists to estimate the strength and mode of natural selection. Although directional and correlational selection gradients are equal to their corresponding regression coefficients, quadratic regression coefficients must be doubled to estimate stabilizing/disruptive selection gradients. Based on a sample of 33 papers published in Evolution between 2002 and 2007, at least 78% of papers have not doubled quadratic regression coefficients, leading to an appreciable underestimate of the strength of stabilizing and disruptive selection. Proper treatment of quadratic regression coefficients is necessary for estimation of fitness surfaces and contour plots, canonical analysis of the gamma matrix, and modeling the evolution of populations on an adaptive landscape.
回归分析的运用对进化生物学家估计自然选择的强度和模式起到了重要作用。尽管定向选择梯度和相关选择梯度等于它们相应的回归系数，但二次回归系数必须翻倍才能估计稳定/分裂选择梯度。基于2002年至2007年发表在《进化》杂志上的33篇论文样本，至少78%的论文没有将二次回归系数翻倍，导致对稳定选择和分裂选择强度的明显低估。对于适应度曲面和等高线图的估计、伽马矩阵的典型分析以及在适应性景观上模拟种群进化而言，正确处理二次回归系数是必要的。
