The era of behavioural big data has created new avenues for data science research, with
many new contributions stemming from academic researchers. Yet data controlled by …

Throughout the coronavirus disease 2019 (COVID-19) pandemic, countries have relied on a
variety of ad hoc border control protocols to allow for non-essential travel while safeguarding …

The widespread availability of cell phones has enabled non-profits to deliver critical health
information to their beneficiaries in a timely manner. This paper describes our work to assist …

Policymakers often choose a policy bundle that is a combination of different interventions in
different dosages. We develop a new technique—treatment variant aggregation (TVA)—to …

The past two decades have witnessed a surge of new research in the analysis of
randomized experiments. The emergence of this literature may seem surprising given the …

Switchback experiments, where a firm sequentially exposes an experimental unit to random
treatments, are among the most prevalent designs used in the technology sector, with …

Factorial designs are widely used to study multiple treatments in one experiment. While t-
tests using a fully-saturated “long” model provide valid inferences,“short” model t-tests (that …

Multi-armed bandit has been well-known for its efficiency in online decision-making in terms
of minimizing the loss of the participants' welfare during experiments (ie, the regret). In …

Contextual bandit algorithms are ubiquitous tools for active sequential experimentation in
healthcare and the tech industry. They involve online learning algorithms that adaptively …

Response-Adaptive Randomization (RAR) is part of a wider class of data-dependent
sampling algorithms, for which clinical trials are typically used as a motivating application. In …