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Related papers: Effect measures for comparing paired event times

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In this paper we review an approach to estimating the causal effect of a time-varying treatment on time to some event of interest. This approach is designed for the situation where the treatment may have been repeatedly adapted to patient…

Statistics Theory · Mathematics 2007-06-13 J. J. Lok , R. D. Gill , A. W. van der Vaart , J. M. Robins

Treatment switching in a randomized controlled trial is said to occur when a patient randomized to one treatment arm switches to another treatment arm during follow-up. This can occur at the point of disease progression, whereby patients in…

Methodology · Statistics 2021-03-24 Andrew Ying , Eric J. Tchetgen Tchetgen

Background: Pleuroparenchymal fibroelastosis (PPFE) is an upper lobe predominant fibrotic lung abnormality associated with increased mortality in established interstitial lung disease. However, the clinical significance of radiologic PPFE…

Software development innovations and advances in computing have enabled more complex and less costly computations in medical research (survival analysis), engineering studies (reliability analysis), and social sciences event analysis…

Applications · Statistics 2020-03-25 Renato Valladares Panaro

I proposed (8, 1, 3) that p values should be supplemented by an estimate of the false positive risk (FPR). FPR was defined as the probability that, if you claim that there is a real effect on the basis of p value from a single unbiased…

Other Statistics · Statistics 2020-08-10 David Colquhoun

What can be considered an appropriate statistical method for the primary analysis of a randomized clinical trial (RCT) with a time-to-event endpoint when we anticipate non-proportional hazards owing to a delayed effect? This question has…

Methodology · Statistics 2023-04-18 José L. Jiménez , Isobel Barrott , Francesca Gasperoni , Dominic Magirr

The onset of several silent, chronic diseases such as diabetes can be detected only through diagnostic tests. Due to cost considerations, self-reported outcomes are routinely collected in lieu of expensive diagnostic tests in large-scale…

Applications · Statistics 2015-09-15 Xiangdong Gu , Yunsheng Ma , Raji Balasubramanian

The use of the non-parametric Restricted Mean Survival Time endpoint (RMST) has grown in popularity as trialists look to analyse time-to-event outcomes without the restrictions of the proportional hazards assumption. In this paper, we…

Methodology · Statistics 2023-11-06 Emily Alger , David S. Robertson , Abigail J. Burdon

Estimation of individual treatment effect in observational data is complicated due to the challenges of confounding and selection bias. A useful inferential framework to address this is the counterfactual (potential outcomes) model which…

Machine Learning · Statistics 2017-01-23 Min Lu , Saad Sadiq , Daniel J. Feaster , Hemant Ishwaran

Tumor response, a binary variable, has historically been the main measure of antitumor activity for many cancer phase II single-arm trials. Simon two-stage designs are often used. Sargent et al. proposed a three-outcome trial design in this…

Methodology · Statistics 2025-03-20 Minghua Shan

Feature screening is an important tool in analyzing ultrahigh-dimensional data, particularly in the field of Omics and oncology studies. However, most attention has been focused on identifying features that have a linear or monotonic impact…

Methodology · Statistics 2023-05-10 Yaxian Chen , KF Lam , Zhonghua Liu

This paper develops a new approach to post-selection inference for screening high-dimensional predictors of survival outcomes. Post-selection inference for right-censored outcome data has been investigated in the literature, but much…

Methodology · Statistics 2021-12-22 Tzu-Jung Huang , Alex Luedtke , Ian W. McKeague

Clinical trials involving novel immuno-oncology (IO) therapies frequently exhibit survival profiles which violate the proportional hazards assumption due to a delay in treatment effect, and in such settings, the survival curves in the two…

Methodology · Statistics 2021-02-02 Nicholas C. Henderson , Kijoeng Nam , Dai Feng

While the inverse probability of treatment weighting (IPTW) is a commonly used approach for treatment comparisons in observational data, the resulting estimates may be subject to bias and excessively large variance when there is lack of…

Methodology · Statistics 2024-02-13 Zhiqiang Cao , Lama Ghazi , Claudia Mastrogiacomo , Laura Forastiere , F. Perry Wilson , Fan Li

Micro-randomized trials are commonly conducted for optimizing mobile health interventions such as push notifications for behavior change. In analyzing such trials, causal excursion effects are often of primary interest, and their estimation…

Methodology · Statistics 2024-08-19 Yihan Bao , Lauren Bell , Elizabeth Williamson , Claire Garnett , Tianchen Qian

The restricted mean survival time (RMST) is the mean survival time in the study population followed up to a specific time point, and is simply the area under the survival curve up to the specific time point. The difference between two RMSTs…

Methodology · Statistics 2025-09-18 Peter Zhang , Brent Logan , Michael Martens

We present a new estimator of the restricted mean survival time in randomized trials where there is right censoring that may depend on treatment and baseline variables. The proposed estimator leverages prognostic baseline variables to…

Statistics Theory · Mathematics 2016-08-22 Iván Díaz , Elizabeth Colantuoni , Daniel F. Hanley , Michael Rosenblum

Survivors of childhood cancer need lifelong monitoring for side effects from radiotherapy. However, longitudinal data from routine monitoring is often infrequently and irregularly sampled, and subject to inaccuracies. Due to this,…

In order to estimate the proportion of `immune' or `cured' subjects who will never experience failure, a sufficiently long follow-up period is required. Several statistical tests have been proposed in the literature for assessing the…

Methodology · Statistics 2026-01-12 Tsz Pang Yuen , Eni Musta

In recurrent survival analysis where the event of interest can occur multiple times for each subject, frailty models play a crucial role by capturing unobserved heterogeneity at the subject level within a population. Frailty models…

Methodology · Statistics 2024-10-30 Borna Bateni , Peyman Bateni , Bishwadeep Bhattacharyya , Devin Reeh
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