惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

A
About on SuperTechFans
有赞技术团队
有赞技术团队
人人都是产品经理
人人都是产品经理
月光博客
月光博客
美团技术团队
博客园 - 聂微东
阮一峰的网络日志
阮一峰的网络日志
WordPress大学
WordPress大学
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
博客园_首页
爱范儿
爱范儿
G
Google Developers Blog
aimingoo的专栏
aimingoo的专栏
T
The Blog of Author Tim Ferriss
MongoDB | Blog
MongoDB | Blog
小众软件
小众软件
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
IT之家
IT之家
I
InfoQ
B
Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
大猫的无限游戏
大猫的无限游戏
T
Tailwind CSS Blog
F
Fortinet All Blogs

stat updates on arXiv.org

A Refined Generalization Analysis for Extreme Multi-class Supervised Contrastive Representation Learning Ensemble Distributionally Robust Bayesian Optimisation The Proxy Presumption: From Semantic Embeddings to Valid Social Measures Modulated learning for private and distributed regression with just a single sample per client device Query-efficient model evaluation using cached responses Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks Optimal Experiments for Partial Causal Effect Identification Order-Agnostic Autoregressive Modelling with Missing Data Grokking or Glitching? How Low-Precision Drives Slingshot Loss Spikes Tuning Derivatives for Causal Fairness in Machine Learning Spherical Flows for Sampling Categorical Data Bayesian Rain Field Reconstruction using Commercial Microwave Links and Diffusion Model Priors GRALIS: A Unified Canonical Framework for Linear Attribution Methods via Riesz Representation Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Unified Framework of Distributional Regret in Multi-Armed Bandits and Reinforcement Learning Jacobian-Velocity Bounds for Deployment Risk Under Covariate Drift Self-Attention as Transport: Limits of Symmetric Spectral Diagnostics Perturbation is All You Need for Extrapolating Language Models Adapt or Forget: Provable Tradeoffs Between Adam and SGD in Nonstationary Optimization Realizable Bayes-Consistency for General Metric Losses Graph Convolutional Support Vector Regression for Robust Spatiotemporal Forecasting of Urban Air Pollution Segmenting Human-LLM Co-authored Text via Change Point Detection Stochastic Schrödinger Diffusion Models for Pure-State Ensemble Generation Understanding Self-Supervised Learning via Latent Distribution Matching The Geometric Mechanics of Contrastive Representation Learning: Alignment Potentials, Entropic Dispersion, and Cross-modal Divergence Imbalanced Classification under Capacity Constraints On the Spectral Structure and Objective Equivalence of Orthogonal Multilabel Fisher Discriminants Partially Observed Structural Causal Models First-Order Efficiency for Probabilistic Value Estimation via A Statistical Viewpoint Robust and Fast Training via Per-Sample Clipping
Index Date Imputation for Survival Analysis in Externally...
[Submitted on 17 Sep 2025 (v1), last revised 16 Jun 2026 (this v · 2026-06-18 · via stat updates on arXiv.org

View PDF HTML (experimental)

Abstract:Externally controlled trials compare outcomes from a single-arm trial with external controls drawn from historical trials, registries, or observational studies. For time-to-event endpoints, a key challenge arises when follow-up is indexed at treatment initiation in the single-arm trial, but the external-control data are indexed at an earlier clinical milestone, such as diagnosis or relapse. This misalignment can induce immortal time bias, distort risk sets, and complicate the interpretation of survival comparisons. We propose Index Date Imputation (IDI), a truncation-aware approach for imputing comparable index dates for external-control patients in settings with delayed treatment initiation. IDI estimates the marginal distribution of treatment-initiation times in the target single-arm population while accounting for the fact that initiation times are observed only among patients who survive long enough to initiate treatment. The imputed index dates are then used to align follow-up and enforce comparable truncation conditions in the external-control cohort. Because temporal alignment alone does not address population-level confounding, IDI is combined with propensity score weighting or matching to improve covariate comparability between cohorts. We evaluate the finite-sample performance of the proposed approach through Monte Carlo simulation studies. Using data from a randomized oncology trial, we emulate an externally controlled analysis with induced index-date misalignment and show that IDI reduces discrepancy from the randomized trial benchmark. IDI provides a practical strategy for index-date alignment in survival analyses involving delayed treatment initiation and can be integrated with standard covariate-adjustment methods when suitable external controls are available.

Submission history

From: Quentin Le Coënt [view email]
[v1] Wed, 17 Sep 2025 17:16:57 UTC (713 KB)
[v2] Tue, 16 Jun 2026 18:01:25 UTC (1,609 KB)