A minimal nontrivial example of higher-order evidence.

Abstract

Higher-order evidence (ie, evidence about evidence) allows epidemiologists and other health data scientists to account for measurement error in validation data. Here, to illustrate the use of higher-order evidence, we provide a minimal nontrivial example of estimating the proportion and show how higher-order evidence can be used to construct sensitivity analyses. The proposed method provides a flexible approach to account for multiple levels of distortion in the results of epidemiologic studies.