Target trial emulation in Stata

This presentation will demonstrate, through an example in Stata, how to conduct a target trial emulation. Target trial emulation is a practical framework that uses observational data to answer causal questions by mimicking a hypothetical randomized clinical trial. In this context, it is essential to control for potential biases and confounding through causal inference methods in order to correctly estimate the causal effect of treatments on the event of interest. Some of the methods that will be discussed and implemented in Stata during the presentation include inverse probability of treatment weighting (IPTW) and the g-formula. Using the comparison of two treatments as an example, the necessary steps to implement an emulated clinical trial will be presented. First, the data will be structured and expanded into a weekly format. Subsequently, different methods will be applied to estimate the causal effect, including a pooled logistic regression model, IPTW, the estimation of adjusted survival curves, and the g-formula. The results will be evaluated under different scenarios to assess how changes in the analytical assumptions affect the findings. The ultimate aim is for attendees to understand how to translate a clinical question into a reproducible, transparent Stata analysis that is consistent with the principles of causal inference.