Added, but didn't test the remaining robustness checks.

[ml_measurement_error_public.git] / simulations / 04_depvar_differential.R

diff --git a/simulations/04_depvar_differential.R b/simulations/04_depvar_differential.R
index df0e825d3d91c543bf8b257c6d6fe56fc65027e0..b3670807549249256da52cfc1fd0cb6ea8662b90 100644 (file)
--- a/simulations/04_depvar_differential.R
+++ b/simulations/04_depvar_differential.R
@@ -76,12 +76,13 @@ parser <- add_argument(parser, "--prediction_accuracy", help='how accurate is th
 parser <- add_argument(parser, "--z_bias", help='how is the classifier biased?', default=1.5)
 parser <- add_argument(parser, "--Bxy", help='coefficient of x on y', default=0.1)
 parser <- add_argument(parser, "--Bzy", help='coeffficient of z on y', default=-0.1)
+parser <- add_argument(parser, "--B0", help='coeffficient of z on y', default=-0.1)
 parser <- add_argument(parser, "--outcome_formula", help='formula for the outcome variable', default="y~x+z")
 parser <- add_argument(parser, "--proxy_formula", help='formula for the proxy variable', default="w_pred~y+z")
 
 args <- parse_args(parser)
 
-B0 <- 0
+B0 <- args$B0
 Bxy <- args$Bxy
 Bzy <- args$Bzy