Dear R-Community,
When writing my master thesis, I faced with difficult issue. Analyzing the
capital structure determinants I have one dependent variable (Total debt
ratio = TD) and 15 independent ones. At the first stage I normalized my
data by deleting outliers from each variable (Pairwise deletion) and in
the result I got every variable to be with different length. Now when
selecting relevant variables for the "best" model, neither stepwise nor
forward or backward procedures don't work perfectly since there are a
number of other combinations of variables wich have also high t-values.
Thus, wichever model I pick, you never know whether this model is
trustworthy. I tried to calculate all possible combinations of independent
variables, but since I have 15 ones, there are thousands of such
combinations and R simply refuses to calculate them! (computer crashes) I
wonder if you can help me to write the code in R in order to find the
model wich include as many variables as it possible with significant
t-values?
cheers, Oleg