Fitting linear models
On Apr 21, 2009, at 12:37 PM, Vemuri, Aparna wrote:
These are all field measured values. For a little background here, I have field measurements of SO4, NO3 and NH4. I used these variables in an atmospheric chemistry model to calculate PBW on a line-by-line basis. To bypass the use of the complex atmospheric chemistry model in the future, I want to develop a regression equation based on the current results I have. Also, I know the atmospheric chemistry model requires SO4, NO3 and NH4 to estimate PBW. So I am using the same as IVs for the regression model. Aparna
One way to create collinearity is to construct a new variable, say PBW?, as a linear combination of the measurements. If you then re- analyze that augmented dataset, you will naturally get the sort of complaints or unexpected behavior from the R interpreter that you are seeing.
David Winsemius