ml_measurement_error_public/simulations/robustness_check_notes.md

robustness_1.RDS

Tests how robust the MLE method for independent variables with differential error is when the model for X is less precise. In the main paper, we include Z on the right-hand-side of the truth_formula. In this robustness check, the truth_formula is an intercept-only model. The stats are in the list named robustness_1 in the .RDS file.

robustness_1_dv.RDS

Like robustness\_1.RDS but with a less precise model for w_pred. In the main paper, we included Z in the outcome_formula. In this robustness check, we do not.

robustness_2.RDS

This is just example 1 with varying levels of classifier accuracy.