A scientist tests a continuous stream of hypotheses over time in the course of her
investigation—she does not test a predetermined, fixed number of hypotheses. The scientist …

Platform trials evaluate multiple experimental treatments under a single master protocol,
where new treatment arms are added to the trial over time. Given the multiple treatment …

The closure principle is fundamental in multiple testing and has been used to derive many
efficient procedures with familywise error rate control. However, it is often unsuitable for …

In contemporary research, data scientists often test an infinite sequence of hypotheses $
H_1, H_2,\ldots $ one by one, and are required to make real-time decisions without knowing …

In recent years, graphical multiple testing procedures have gained popularity due to their
generality and ease of interpretation. In contemporary research, online error control is often …

In this paper, we consider online multiple testing with familywise error rate (FWER) control,
where the probability of committing at least one type I error will remain under control while …

We consider the problem of online local false discovery rate (FDR) control where multiple
tests are conducted sequentially, with the goal of maximizing the total expected number of …

We provide new nonasymptotic false discovery proportion (FDP) confidence envelopes in
several multiple testing settings relevant for modern high dimensional-data methods. We …

We consider the problem of sequential multiple hypothesis testing with nontrivial data
collection cost. This problem appears, for example, when conducting biological experiments …

In online multiple testing, an a priori unknown number of hypotheses are tested sequentially,
ie at each time point a test decision for the current hypothesis has to be made using only the …