Belovsky Gary E
Ecology Center and Department of Fisheries and Wildlife, Utah State University, 84322-5210, Logan, UT, USA.
Oecologia. 1994 Dec;100(4):475-480. doi: 10.1007/BF00317870.
Linear programming models of diet selection (LP) have been criticized as being too sensitive to variations in parameter values that have not been or may not be able to be measured with a high degree of precision (small standard error). Therefore, LP's predictions have been questioned, even though the predicted diet choices agree very well with observations in 400 published tests. The philosophical and statistical aspects of this criticism of LP are reviewed in light of the ability to test any nontrivial ecological theory. It is argued that measures of error in field data may not meet simple statistical definitions, and thereby, may make sensitivity analyses that use the error measures overly conservative. Furthermore, the important issue in testing ecological theory may not be the statistical confidence in a single test, but whether or not the theory withstands repeated tests.
饮食选择的线性规划模型(LP)一直受到批评,因为它对那些尚未或可能无法高精度测量(小标准误差)的参数值变化过于敏感。因此,尽管在400项已发表的测试中,LP预测的饮食选择与观察结果非常吻合,但其预测仍受到质疑。鉴于检验任何重要生态理论的能力,本文对这种对LP的批评所涉及的哲学和统计学方面进行了审视。有人认为,实地数据中的误差度量可能不符合简单的统计学定义,从而可能使使用这些误差度量的敏感性分析过于保守。此外,检验生态理论的重要问题可能不在于单次测试中的统计置信度,而在于该理论是否经得起反复检验。