The M-survival learner estimates heterogeneous indirect treatment effects in censored survival data and supplies a new criterion to detect mediation heterogeneity for surrogate endpoint validation.
For spherical and well-separated data, our theorem below shows that t-SNE with early exaggeration succeeds in finding a full visualization
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Modeling Heterogeneous Mediation Effects in Survival Analysis via an Interpretable M-Learner Framework
The M-survival learner estimates heterogeneous indirect treatment effects in censored survival data and supplies a new criterion to detect mediation heterogeneity for surrogate endpoint validation.