Physical Sciences and Mathematics Commons^™

Adjustment Uncertainty In Effect Estimation, Ciprian M. Crainiceanu, Francesca Dominici, Giovanni Parmigiani

Johns Hopkins University, Dept. of Biostatistics Working Papers

The selection of confounders and their functional relationship with the out- come affects exposure effect estimates. In practice, there is often substantial uncertainty about this selection, which we define here as “adjustment uncertainty.” We address the problem of estimating the effect of exposure on an outcome with focus on quantifying the effect of unknown confounders from a large set of potential confounders. We propose a general statistical framework for handling adjustment uncertainty in exposure effect estimation, a specific implementation called "Structured Estimation under Adjustment Uncertainty (STEADy)", and associated visualization tools. Theoretical results and simulation studies show that STEADy consistently estimates …