I am using indicator regression with an interaction term to compare the slopes to two groups.
Here is the form of the equation:
$Y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + + \beta_3 X_1 X_2$
$X_2 $ is my dummy variable (1 or 0).
Based on how I set up the regression:
When $X_2 = 0$, then the $slope_0 = \beta_1 $.
When $X_2 = 1$, then the $slope_1 = \beta_1 + \beta_3 $.
What I would like to determine is whether there is a test to determine whether $slope_1$ is significantly different than zero? I know I can split the dataset into two (based on the dummy variable) and regress separately to determine whether $slope_1$ is significantly different than zero, but could I could determine this without the separate regression? Is there a test for this in R?