Hello. First time posting. I used geom_abline() to plot a family of lines created with random slopes and intercepts. They make a bowtie pattern with the "knot" on the y-intercept. I would like to translate the "knot" to be at x = mean(var_1) instead of on x=0 so that the intercept a represents the expected value of var_2 when var_1 is at its mean. This should be easy but I can't seem to think of a simple way to do it. If I was working with the full formula for a line it would just be y = b(x - mean(var_1)) + a, but with ablines you only provide a,b and the x's are provided from the x-axis so I don't know how to manipulate them. Perhaps I'm using the wrong geom? Thank you in advance for any help.
set.seed(1237) n <- 30 mean_of_var_1 = 37 a <- rnorm(n, 37, 1) b <- rnorm(n, 0, .6) test_tbl <- tibble( a_intercept = a, b_slope = b) test_tbl %>% ggplot() + geom_abline(intercept = a, slope = b) + ylim(c(0,100)) + xlim(c(0,100)) + labs( x = "var_1", y = "var_2" )