35

ECOM II

The results of the multicollinearity test are presented in a tabbed sheet.

A multiple regression is undertaken for each of the environmental variables in turn

with all the other environmental variables acting as the independent variables. Values

of R squared close to 1 or Variance inflation factors (VIF) well above 1 are indicative

of multicollinearity and you should consider removing one of a group of highly

correlated variables from the analysis. High VIF values are highlighted in red. Use

stepwise regression

 and 

Variable Selection

 to identify which environmental variables

to retain for your analysis

If you should obtain very large values for VIF it is likely that some of your variables

add up to a constant. This often happens if you are using dummy variables see

Linear Combinations of Environmental Variables

.

7.7

Circular environmental variables

Two common examples of circular data are direction (aspect) and day of the year.

Aspect (or compass direction of a slope) can be transformed by trigonometric

functions (Roberts 1986). The simplest way to do this is to create two variables,

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