The impact of parametric assumptions on the bias-variance tradeoff for causal analysis of time-to-event outcomes

The choice of parametric assumptions in survival analysis models for time-to-event outcomes involves a fundamental bias-variance trade-off, but the practical implications of this trade-off for causal analyses of real-world treatment effects had not been systematically examined.

Target RWE researchers presented a systematic examination of how parametric model specification choices affect the bias-variance trade-off in causal time-to-event analyses, characterizing the conditions under which flexible versus restrictive models are preferable.

Providing guidance on parametric model selection for time-to-event causal analyses enables Target RWE and pharma partners to make principled analytic choices that minimize bias while maintaining appropriate variance.

Parametric model selection guidance for bias-variance trade-off in causal time-to-event analyses, Survival analysis methodology for regulatory-grade RWE treatment effectiveness programs