Application of robust regression to the analysis of BMP effects in paired watersheds

A routine is developed in which known information from the pre-BMP phase of a paired watershed monitoring project is used to make inferences about the minimum level of change that would be significant after a specified duration of post-BMP monitoring, or to determine the minimum duration of post-BMP monitoring to be able to detect a specified level of change. In addition to the usual least squares regression procedure, the routine estimates the linear relationship using the reweighted least squares procedure, a robust (nonparametric) procedure that reduces the effects of outliers. In some instances, the reweighted least squares procedure results in an increased sensitivity of the statistical procedures for detecting change. -from Authors