In this talk, I will present a bias correction estimator called the ricochet. Bias can arise for many reasons: such as biased sampling, model misspecification; data censoring or truncation; or post hoc selection of positive results. In finite samples, bias can also occur as an intrinsic property of an estimator even when none of these problems are present. The ricochet was developed to remove...