Abstract This paper is focused on detailed aspects of the loss function rho and its derivative psi for an optimal bias … robust regression method that minimizes the maximum asymptotic bias subject to a constraint on normal distribution efficiency … the following aspects the optimal bias robust regression estimator: (1) The analytic form for the rho function; (2) A …

performance criteria for outlier identifiers. One of those Criteria, the maximum asymptotic bias, is carried over here to … identifiers with bounded maximum asymptotic bias. …

model. All three estimators have the same breakdown point, but their explosion bias curves are different. It is shown that … under a gross error model the explosion bias curve of the new estimator performs better than the bias curves of the other …

. Mendelian randomization studies are known to be affected by both weak instrument bias and the pleiotropic bias that arises when … Understanding Society, we find no evidence for pleiotropic bias, and the negative effect of body mass index on income to be around …

sheds light on the connection between both approaches. I provide alternative formulas (approximations) for the bias and …-robust standard errors in RD settings. Bias mitigation approaches are discussed and a novel, bootstrap higher-order bias correction …

to hold. In this paper we propose a crude analytical approach to study the large sample bias of estimators when all … normalized weights leads to a smaller bias compared to a simple IPW estimator. To analyze the question of when the use of two … misspecified models are better than one we derive necessary and sufficient conditions for when the DR estimator has a smaller bias …