Using the best_linear_projection to get coefficient estimates for treatment and control separately

[aczura2024]

I am fitting a causal forest with 2 treatment arms and want to use the best_linear_projection() function to estimate the regression coefficients on the treatment and control groups separately. When I make a separate matrix corresponding to the observations solely in the treatment group, I get an error Error in best_linear_projection(mycrf, A = treat_covar[, 2:ncol(treat_covar)]) :
The number of rows of A does not match the number of training examples.

Any ideas?