Dual Role for Negative Control Outcomes: Improving Validity and Efficiency in Observational Studies

Music City Center 

Negative control outcomes (NCOs) are increasingly used in observational studies to detect and correct bias, particularly in settings where unmeasured confounding poses a challenge to causal inference. While previous applications of NCOs have primarily focused on bias correction, their potential to improve the efficiency of treatment effect estimation remains underexplored. In this work, we propose a novel method that leverages NCOs not only to adjust for bias but also to enhance statistical efficiency. Through extensive simulations, we demonstrate that our approach can reduce the standard deviation of the estimated treatment effect up to 60% while maintaining unbiased estimation. To illustrate its practical utility, we apply the method to evaluate the impact of GLP-1 receptor agonists (GLP1RAs) on mental health disorders. Our findings highlight the dual benefits of NCOs in improving both validity and precision in causal effect estimation.

Efficiency Gain

GLP-1 receptor agonists

Negative Control Outcomes

Observational Studies 

Section on Statistics in Epidemiology