I have a set of records from 68 different watersheds that previously mined but reclaimed later. After some years a portion of mined area were converted to forest and there was no difference between unmined sites and reclaimed forest areas.
I am trying to conduct a regression analysis to predict stream conductivity (dependent variable) and my independent variables are reclamation age (year), reclaimed forest area(%) and mined area(%). I ran stepwise multivariate regression in SPSS. It results reclaimed forest was not a significant predictor but only reclamation age and mined area were significant and R-square for the model 0.81.
Then I created another independent variable called mined area without reclaimed forest. Basically I removed reclaimed forest areas from mined areas. I ran the regression model again. Reclamation age and mined w/o rec forest as Independent variable while conductivity was dependent variable. It improved my R-square 0.83.
As a conclusion, even though there was no direct correlation between reclaimed forest areas and conductivity, taking reclaimed forest areas out and running the model again improved my R-square value. So, I would like to ask, Is it OK to do that? I would like to use this in a scientific project. here is model summary and coefficients