I am trying to calculate the minimum detectable effect size (MDE) of an explanatory variable in a multiple linear regression.
The regression looks like the following: $$ y_i = \beta_0 + \beta_1X_1 + \beta_2*X_2 + \beta_3*X_3 + \beta_4*X_4 + \epsilon_i $$ whereby I am only interested in the MDE of $X_1$ in this multiple linear regression.
I have found code for linear regression in R: pwr.f2.test().
However, I am not sure if this can eliminate the minimum detectable effect size for one variable. Does anyone know how to get the minimum detectable effect size of one explanatory variable in a multiple linear regression? How can I implement this in R?