Alias Coefficient
When you run a Linear Regression model in R, sometimes you see NAs in the model output.
This happens because the variable is linearly dependent on other variables.
''alias'' refers to the variables that are linearly dependent on others (i.e. cause perfect multicollinearity).
See the example below.
library(datasets); data(swiss); require(stats); require(graphics) z <- swiss$Agriculture + swiss$Education
So in this case ‘z’ doesn’t help us in predicting Fertility since it doesn’t give us any more information that we can’t already get from ‘Agriculture’ and ‘Education’.
fit = lm(Fertility ~ . + z, data = swiss)
> alias(fit) Model : Fertility ~ Agriculture + Examination + Education + Catholic+ Infant.Mortality + z
Complete : (Intercept) Agriculture Examination Education Catholic Infant.Mortality z 0 1 0 1 0 0
When we notice that there’s an NA coefficient in our model we can choose to exclude that variable and the model will still have the same coefficients as before
