A Minimal Nontrivial Example of Higher Order Evidence

Higher order evidence (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.