Stepwise Multiple Linear Regression

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Step 1   Shows the effect of including all the explanatory variables into the model,

with the individual p values.

Step 2   Shows the effect of removing the least explanatory variable from the model.

...and so on.

In most species/environmental datasets it is unusual for more than three variables to

be included in any explanatory model.

A common problem with environmental data sets is that of 

multicollinearity

 between

explanatory variables. ECOM automatically checks for multicollinearity and, if

detected, will take to you a screen that details the problem and allows you to remove

one of the correlated variables.

Copyright 2004  PISCES Conservation Ltd