[R] model parameters: independent enough?

[Dylan Beaudette]

Hi,

Is there a good approach to working with multiple predictors in a linear model 
which are in some ways related? In other words, is there a procedure, test, 
or general rule for determining if predictor variables are "independent 
enough"?

An example from soil science could be the notion of sand, silt and clay 
fractions- all adding to 100% In many cases both sand and clay content are 
useful predictors, however they are "linked" through their relationship with 
the remaining silt fraction (always adding to 100%). Although there is a 
zero-sum relationship between these three fractions, a single fraction rarely 
dominates the others. 

would range of cor(sand, clay) give me reason to through out one of them as a 
predictor in a linear model?

thanks in advance,



-- 
Dylan Beaudette
Soil Resource Laboratory
http://casoilresource.lawr.ucdavis.edu/
University of California at Davis
530.754.7341