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The proportional hazards assumption in the commonly used Cox model for censored failure time data is often violated in scientific studies. Yang and Prentice (2005) proposed a novel semiparametric two-sample model that includes the…

Methodology · Statistics 2012-06-06 Guoqing Diao , Donglin Zeng , Song Yang

Left censoring can occur with relative frequency when analysing recurrent events in epidemiological studies, especially observational ones. Concretely, the inclusion of individuals that were already at risk before the effective initiation…

Methodology · Statistics 2021-02-24 Gilma Hernández-Herrera , David Moriña , Albert Navarro

Existing survival analysis techniques heavily rely on strong modelling assumptions and are, therefore, prone to model misspecification errors. In this paper, we develop an inferential method based on ideas from conformal prediction, which…

Methodology · Statistics 2023-04-25 Emmanuel J. Candès , Lihua Lei , Zhimei Ren

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

This paper focuses on modelling surrender time for policyholders in the context of life insurance. In this setup, a large lapse rate at the first months of a contract is often observed, with a decrease in this rate after some months. The…

Applications · Statistics 2022-07-18 Viviana G. R. Lobo , Thais C. O. Fonseca , Mariane B. Alves

In this paper, we establish weak consistency and asymptotic normality of an M-estimator of the regression function for left truncated and right censored (LTRC) model, where it is assumed that the observations form a stationary alpha-mixing…

Statistics Theory · Mathematics 2023-05-09 Hassiba Benseradj , Zohra Guessoum

Patient care may be improved by recommending treatments based on patient characteristics when there is treatment effect heterogeneity. Recently, there has been a great deal of attention focused on the estimation of optimal treatment rules…

Methodology · Statistics 2024-01-29 Michael Jetsupphasuk , Michael G. Hudgens , Jessie K. Edwards , Stephen R. Cole

The Weibull distribution is one of the most used tools in reliability analysis. In this paper, assuming a Bayesian approach, we propose necessary and sufficient conditions to verify when improper priors lead to proper posteriors for the…

Statistics Theory · Mathematics 2020-05-19 Eduardo Ramos , Pedro L. Ramos

This paper considers the problem of semi-parametric proportional hazards model fitting for interval, left and right censored survival times. We adopt a more versatile penalized likelihood method to estimate the baseline hazard and the…

Methodology · Statistics 2019-04-16 Jun Ma , Dominique-Laurent Couturier , Stephane Heritier , Ian Marschner

This paper considers the three-parameter exponentiated Weibull family under type II censoring. It first graphically illustrates the shape property of the hazard function. Then, it proposes a simple algorithm for computing the maximum…

Methodology · Statistics 2011-02-03 Lianfen Qian

Competing risks data refer to situations where the occurrence of one event pre- cludes the possibility of other events happening, resulting in multiple mutually exclusive events. This data type is commonly encountered in medical research…

Methodology · Statistics 2025-10-21 Fatemeh Mahmoudi , Chenxi Li , Kaida Cai , Xuewen Lu

In this paper, we predict conditional survival functions through a combined regression strategy. We take weak learners as different random survival trees. We propose to maximize concordance in the right-censored set up to find the optimal…

Machine Learning · Statistics 2022-10-12 Rahul Goswami , Arabin Kumar Dey

The subject of tail estimation for randomly censored data from a heavy tailed distribution receives growing attention, motivated by applications for instance in actuarial statistics. The bias of the available estimators of the extreme value…

Methodology · Statistics 2017-05-19 Jan Beirlant , Gaonyalelwe Maribe , Andrehette Verster

This paper extends doubly robust censoring unbiased transformations to a broad class of censored data structures under the assumption of coarsening at random and positivity. This includes the classic survival and competing risks setting,…

Methodology · Statistics 2024-11-08 Oliver Lunding Sandqvist

We introduce a kernel-based goodness-of-fit test for censored data, where observations may be missing in random time intervals: a common occurrence in clinical trials and industrial life-testing. The test statistic is straightforward to…

Methodology · Statistics 2018-10-11 Tamara Fernández , Arthur Gretton

This paper considers estimation and inference about tail features when the observations beyond some threshold are censored. We first show that ignoring such tail censoring could lead to substantial bias and size distortion, even if the…

Econometrics · Economics 2020-02-25 Yulong Wang , Zhijie Xiao

Proper econometric analysis should be informed by data structure. Many forms of financial data are recorded in discrete-time and relate to products of a finite term. If the data comes from a financial trust, it will often be further subject…

Statistics Theory · Mathematics 2024-12-24 Jackson P. Lautier , Vladimir Pozdnyakov , Jun Yan

The two-parameter Birnbaum-Saunders distribution has been used succesfully to model fatigue failure times. Although censoring is typical in reliability and survival studies, little work has been published on the analysis of censored data…

Methodology · Statistics 2011-11-22 Artur J. Lemonte , Silvia L. P. Ferrari

Biomarker data is often subject to limits of quantification and/or limits of detection. Statistically, this corresponds to left- or interval-censoring. To be able to associate a censored time-to-event endpoint to a biomarker covariate, the…

Computation · Statistics 2014-04-29 Stanislas Hubeaux , Kaspar Rufibach

Time-to-event modelling, known as survival analysis, differs from standard regression as it addresses censoring in patients who do not experience the event of interest. Despite competitive performances in tackling this problem, machine…

Machine Learning · Computer Science 2023-05-12 Vincent Jeanselme , Chang Ho Yoon , Brian Tom , Jessica Barrett