The Setup: I am performing an exhaustive search of multiple linear regression models with the R package leaps. The package does return vectors of certain fit statistics (i.e. BIC and r-squared). However, there are a few other fit criteria (i.e. CCC) I would like to generate for a subset of the models (~100). Instead of fitting the subset of models manually, I want to leverage a data.frame provided by leaps for automated refitting of predictive multiple linear models.
The Challenge: How can I code a FOR loop (or some other function) to refit linear models? I have two data.frames to use: 1) the data (response + all explanatory variables) and 2) a data.frame describing what variables where in each model. The second data.frame has boolean (TRUE/FALSE) indicators of whether each explanatory variable (columns) was incorporated in the linear model (rows). Below is a representation of that data.frame.
(Intercept) var1 var2 var3 X5 TRUE TRUE FALSE FALSE X6 TRUE TRUE FALSE FALSE X7.2 TRUE TRUE FALSE FALSE X7.4 TRUE TRUE FALSE FALSE X8.2 TRUE TRUE FALSE TRUE
My major hang up is I don't know how to automate generating a formula that works for the lm function.
In advance, thank you all for your help.