Assistant Professor Lu Mao was awarded a three-year National Science Foundation grant titled “Randomized Trials with Non-Compliance: Extending the Angrist-Imbens-Ruben Framework.
Congratulations to Lu!
Randomized controlled trial (RCT) refers to a design commonly employed by clinical and sociological studies where study participants are randomly assigned to an investigational treatment arm, or to a control arm to serve as comparison. With randomization as the unique device to eliminate systematic bias in treatment choice, RCT has been rightfully enshrined as the gold standard for any scientific inquiry, especially those involving human subjects. A challenging yet pervasive issue arises, however, when some participants in an RCT do not comply with the random assignment and instead self-select into the treatment of their choice. This self-selection compromises the objectivity of treatment assignment and thereby weakens the rigor of the experiment. A seminal paper by Angrist, Imbens, and Rubin (1996) provided invaluable insight into the difficult task of drawing valid causal inference in RCTs plagued by non-compliance. However, their work is focused on the average of a quantitative outcome as the metric of treatment effect and thus does not apply to other commonly encountered outcome types such as ordinal data (e.g., tumor grade). Moreover, it is unclear whether their approach has utilized the available information on each participant to the fullest extent. With the advent of modern statistical/mathematical tools such as empirical processes, semiparametric theory, and functional analysis, the PI revisits and seeks to extend the Angrist-Imbens-Rubin (AIR) approach by targeting a much wider scope of effect size measures, or causal estimands, and studying their efficient estimation under a unified framework. The PI also plans to develop user-friendly software packages implementing the corresponding inference procedures and involve graduate students in the project. Successful completion of this project will equip investigators with more versatile and powerful tools to address non-compliance in RCTs, the mainstay of medical and sociological investigations.