Diane Uschner, George Washington University.
Title: Randomization tests toaddress disruptions inclinical trials
Abstract: In early 2020, the World Health Organization declared the novel corona virus disease (COVID-19) a pandemic. On top of prompting various trials to study treatments and vaccines for COVID-19, COVID-19 also had numerous consequences for ongoing clinical trials. People around the globe restricted their daily activities to minimize contagion, which led to missed visits and cancelling or postponing of elective medical treatments. For some clinical indications, COVID-19 may lead to a change in the patient population or treatment effect heterogeneity. We will measure the effect of the disruption on randomization tests and derive a methodological framework for randomization tests that allows for the assessment of clinical trial disruptions. We show that randomization tests are robust against clinical trial disruptions in certain scenarios, namely if the disruption can be considered an ancillary statistic to the treatment effect. As a consequence, randomization tests maintain type I error probability and power at their nominal levels.