Invited Commentary: Quantitative Bias Analysis Can See the Forest for the Trees

Abstract

The accompanying article by Jiang et al. (Am J Epidemiol. 2021;190(9):1830-1840) extends quantitative bias analysis from the realm of statistical models to the realm of machine learning algorithms. Given the rooting of statistical models in the spirit of explanation and the rooting of machine learning algorithms in the spirt of prediction, this extension is thought-provoking indeed. Some such thoughts are expounded upon here.

Keywords: machine learning; measurement error; misclassification; quantitative bias analysis; random forests.