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Related papers: Modified Cox regression with current status data

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Palliative medicine is an interdisciplinary specialty focusing on improving quality of life (QOL) for patients with serious illness and their families. Palliative care programs are available or under development at over 80% of large US…

This paper studies identification and inference in transformation models with endogenous censoring. Many kinds of duration models, such as the accelerated failure time model, proportional hazard model, and mixed proportional hazard model,…

Econometrics · Economics 2021-07-05 Shosei Sakaguchi

Reliable uncertainty quantification is essential in survival prediction, particularly in clinical settings where erroneous decisions carry high risk. Conformal prediction has attracted substantial attention as it offers a model-agnostic…

Methodology · Statistics 2025-12-04 Jaeyoung Shin , Chi Hyun Lee , Sangwook Kang

Interval censoring arises frequently in clinical, epidemiological, financial, and sociological studies, where the event or failure of interest is known only to occur within an interval induced by periodic monitoring. We formulate the…

Methodology · Statistics 2016-03-01 Donglin Zeng , Lu Mao , D. Y. Lin

Background: The hazard ratio of the Cox proportional hazards model is widely used in randomized controlled trials to assess treatment effects. However, two properties of the hazard ratio including the non-collapsibility and built-in…

Methodology · Statistics 2024-01-17 Helen Bian , Menglan Pang , Guanbo Wang , Zihang Lu

The instability in the selection of models is a major concern with data sets containing a large number of covariates. This paper deals with variable selection methodology in the case of high-dimensional problems where the response variable…

Applications · Statistics 2012-03-23 Marie Walschaerts , Eve Leconte , Philippe Besse

We propose a method to quantify uncertainty around individual survival distribution estimates using right-censored data, compatible with any survival model. Unlike classical confidence intervals, the survival bands produced by this method…

Methodology · Statistics 2025-12-18 Matteo Sesia , Vladimir Svetnik

The partial linear Cox model for interval-censoring is well-studied under the additive assumption but is still under-investigated without this assumption. In this paper, we propose to use a deep ReLU neural network to estimate the…

Methodology · Statistics 2023-07-04 Jie Zhou , Yue Zhang , Zhangsheng Yu

Survival Analysis (SA) constitutes the default method for time-to-event modeling due to its ability to estimate event probabilities of sparsely occurring events over time. In this work, we show how to improve the training and inference of…

Machine Learning · Computer Science 2023-12-12 Chris Solomou

Time-to-event semi-competing risk endpoints may be correlated when both events are occurring on the same individual. These events and the association between them may also be influenced by individual characteristics. In this paper, we…

Methodology · Statistics 2023-04-07 Yinghui Wei , Malgorzata Wojtys , Lexy Sorrell , Peter Rowe

IMPORTANCE: Feature selection with respect to time-to-event outcomes is one of the fundamental problems in clinical trials and biomarker discovery studies. But it's unclear which statistical methods should be used when sample size is small…

Methodology · Statistics 2022-10-17 Rong Lu

Studies of the effects of medical interventions increasingly take place in distributed research settings using data from multiple clinical data sources including electronic health records and administrative claims. In such settings, privacy…

Methodology · Statistics 2021-01-06 Martijn J. Schuemie , Yong Chen , David Madigan , Marc A. Suchard

Thomas' partial likelihood estimator of regression parameters is widely used in the analysis of nested case-control data with Cox's model. This paper proposes a new estimator of the regression parameters, which is consistent and…

Statistics Theory · Mathematics 2007-06-13 Kani Chen

The Cox proportional hazards model is a canonical method in survival analysis for prediction of the life expectancy of a patient given clinical or genetic covariates -- it is a linear model in its original form. In recent years, several…

Machine Learning · Statistics 2022-08-23 Xuelin Yang , Louis Abraham , Sejin Kim , Petr Smirnov , Feng Ruan , Benjamin Haibe-Kains , Robert Tibshirani

This paper presents a conformal prediction procedure to generate two-sided or one-sided prediction intervals for survival times in the presence of right censoring. Specifically, the method provides two-sided predictive bounds for…

Methodology · Statistics 2025-06-23 Chris Holmes , Ariane Marandon

In the study of life tables the random variable of interest is usually assumed discrete since mortality rates are studied for integer ages. In dynamic life tables a time domain is included to account for the evolution effect of the hazard…

Methodology · Statistics 2021-12-21 Luis E. Nieto-Barajas

In this paper, we make an experimental comparison of semi-parametric (Cox proportional hazards model, Aalen's additive regression model), parametric (Weibull AFT model), and machine learning models (Random Survival Forest, Gradient Boosting…

Machine Learning · Computer Science 2020-03-20 Camila Fernandez , Chung Shue Chen , Pierre Gaillard , Alonso Silva

In two harmonized efficacy studies to prevent HIV infection through multiple infusions of the monoclonal antibody VRC01, a key objective is to evaluate whether the serum concentration of VRC01, which changes cyclically over time along with…

Methodology · Statistics 2018-01-26 Yunda Huang , Yuanyuan Zhang , Zong Zhang , Peter B. Gilbert

Imputation is a popular approach to handling censored, missing, and error-prone covariates -- all coarsened data types for which the true values are unknown. However, there are nuances to imputing these different data types based on the…

Methodology · Statistics 2025-04-29 Sarah C. Lotspeich , Ethan M. Alt

We consider a non-proportional hazards model where the regression coefficient is not constant but piecewise constant. Following Andersen and Gill (1982), we know that a knowledge of the changepoint leads to a relatively straightforward…

Applications · Statistics 2016-10-11 Roxane Duroux , John O'Quigley
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