X-Git-Url: https://code.communitydata.science/ml_measurement_error_public.git/blobdiff_plain/8ac33c14d7e7874bf283aa9c252fa06566dc8b15..c45ea9dfebca86dfddc1e9237aa74866c5166519:/simulations/robustness_check_notes.md

diff --git a/simulations/robustness_check_notes.md b/simulations/robustness_check_notes.md
index 0a287a7..64a472d 100644
--- a/simulations/robustness_check_notes.md
+++ b/simulations/robustness_check_notes.md
@@ -10,5 +10,31 @@ Like `robustness\_1.RDS` but with a less precise model for $w_pred$.  In the mai
 
 # robustness_2.RDS
 
-This is just example 1 with varying levels of classifier accuracy. 
+This is just example 1 with varying levels of classifier accuracy indicated by the `prediction_accuracy` variable.. 
+
+# robustness_2_dv.RDS
+
+Example 3 with varying levels of classifier accuracy indicated by the `prediction_accuracy` variable.
+
+# robustness_3.RDS
+
+Example 1 with varying levels of skewness in the classified variable. The variable `Px` is the baserate of $X$ and controls the skewness of $X$.
+It probably makes more sense to report the mean of $X$ instead of `Px` in the supplement.
+
+# robustness_3_dv.RDS
+
+Example 3 with varying levels of skewness in the classified variable. The variable `B0` is the intercept of the main model and controls the skewness of $Y$.
+It probably makes more sense to report the mean of $Y$ instead of B0 in the supplement. 
+
+# robustness_4.RDS
+
+Example 2 with varying amounts of differential error. The variable `y_bias` controls the amount of differential error.
+It probably makes more sense to report the corrleation between $Y$ and $X-~$, or the difference in accuracy from when when $Y=1$ to $Y=0$ in the supplement instead of `y_bias`.
+
+# robustness_4_dv.RDS
+
+Example 4 with varying amounts of bias. The variable `z_bias` controls the amount of differential error.
+It probably makes more sense to report the corrleation between $Z$ and $Y-W$, or the difference in accuracy from when when $Z=1$ to $Z=0$ in the supplement instead of `z_bias`.
+
+