cleaning up + implementing robustness checks

[ml_measurement_error_public.git] / simulations / robustness_check_notes.md

# robustness_1.RDS

Tests how robust the MLE method is when the model for $X$ is less precise. In the main result, we include $Z$ on the right-hand-side of the `truth_formula`. 
In this robustness check, the `truth_formula` is an intercept-only model.