# A Targeted Learning Framework for Estimating Restricted Mean Survival Time Difference using Pseudo-observations

arXiv: https://arxiv.org/abs/2601.06296 · HTML: https://mlsanity.com/paper/2601.06296/

## Key facts

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- First posted on arXiv 9 Jan 2026.

## Abstract (arXiv)

A targeted learning (TL) framework is developed to estimate the difference in the restricted mean survival time (RMST) for a clinical trial with time-to-event outcomes. The approach starts by defining the target estimand as the RMST difference between investigational and control treatments. Next, an efficient estimation method is introduced: a targeted minimum loss estimator (TMLE) utilizing pseudo-observations. Moreover, a version of the copy reference (CR) approach is developed to perform a sensitivity analysis for right-censoring. The proposed TL framework is demonstrated using a real data application.