Regression and model-building in conservation biology, biogeography and ecology: The distinction between and reconciliation of 'predictive' and 'explanatory' models
Regression and model-building in conservation biology, biogeography and ecology: The distinction between and reconciliation of 'predictive' and 'explanatory' models
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DOI：
10.1023/a:1008985925162
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发表时间：
2000-05-01
影响因子：
3.4
通讯作者：
Mac Nally, R
中科院分区：
文献类型：
--
作者：
Mac Nally, R
在许多大规模的保护或生态问题中，实验是棘手的或不道德的，回归方法被用来试图衡量一组名义上的自变量（X）对因变量（Y）的影响。工作人员通常希望断言给定的X对Y有重大影响，因此，通过使用这种间接来推断可能的因果关系。除了可论证性问题本身之外，还有两个困难：（1）多元回归受到X中共线关系的困扰;（2）任何回归都旨在产生一个函数，该函数以某种方式最小化观察到的Y和“预测”Y之间的总体差异，这并不一定等同于确定多变量设置中可能的影响。问题（1）可以通过比较两种途径来探索，一种是寻找单一的“最佳”回归模型，另一种是同时考虑所有可能的回归模型。有人建议，如果这两种方法不同意的独立变量可能是“重要的”，那么扣除必须受到怀疑。
In many large-scale conservation or ecological problems where experiments are intractable or unethical, regression methods are used to attempt to gauge the impact of a set of nominally independent variables (X) upon a dependent variable (Y). Workers often want to assert that a given X has a major influence on Y, and so, by using this indirection to infer a probable causal relationship. There are two difficulties apart from the demonstrability issue itself: (1) multiple regression is plagued by collinear relationships in X; and (2) any regression is designed to produce a function that in some way minimizes the overall difference between the observed and 'predicted' Ys, which does not necessarily equate to determining probable influence in a multivariate setting. Problem (1) may be explored by comparing two avenues, one in which a single 'best' regression model is sought and the other where all possible regression models are considered contemporaneously. It is suggested that if the two approaches do not agree upon which of the independent variables are likely to be 'significant', then the deductions must be subject to doubt.