I am building a predictive model with 6 continuous independent variables. I’m trying to select the key variables among these variables to build the model. However, there is collinearity between three of the variables.
So, with small changes in data, I get very different results and interpretations. The variables which are significant on one subset of data don’t remain significant on other subsets. This is causing a lot of confusion and I don’t know how to explain this to my stakeholders.
I am using SAS to build this model. Can you suggest me the efficient methods to deal with it?