G-computation for policy-relevant effects of interventions on time-to-event outcomes

G-computation is a powerful tool for estimating policy-relevant causal effects of time-varying interventions on time-to-event outcomes, but practical implementation guidance including estimation, variance, and interpretation was not available in an accessible reference.

Target RWE researchers and UNC collaborators published a methodological paper providing accessible implementation guidance for g-computation applied to policy-relevant causal effects of interventions on time-to-event outcomes.

Providing accessible g-computation guidance for time-to-event outcomes advances practical adoption of this method in Target RWE's analytic toolkit, supporting capability to estimate causal effects of complex interventions for pharma partners with survival endpoint studies.

G-computation implementation guidance for policy-relevant causal effects on time-to-event outcomes, Advanced causal methods toolkit development supporting pharma partner survival analysis studies