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Arditi, R.
Avoiding fallacious significance tests in stepwise regression: a monte carlo method applied to a meteorological theory for the Canadian lynx cycle
1989 International Journal of Biometeorology (33(1)): 24-26
Stepwise regression is often used in ecology to identify critical factors. From a large number of possible predictors, the procedure selects the subset generating the highest coefficient of determination, R2. This work presents a method of testing the significance of this coefficient. Monte Carlo simulations are used to calculate the statistical distribution of R2 under the null hypothesis that the response variable is independent of the predictors. The method is illustrated by an application to a previously published analysis of the Canadian lynx population cycle where more than 75% of the variance could be explained by four meteorological factors.
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