Stepwise Multiple Linear Regression
54
Step 1   Shows the effect of introducing the most explanatory variable into the model,
and a list of candidate variables that will be entered next, providing they fit the
selection criteria.
Step 2   Shows the effect of introducing the next most explanatory variable into the
model, and a list of candidate variables that will be entered next, providing they fit
the selection criteria.
...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
Copyright 2004  PISCES Conservation Ltd





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