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This paper proposes a stochastic approach to model temperature dynamic and study related risk measures. The dynamic of temperatures can be modelled by a mean-reverting process such as an Ornstein-Uhlenbeck one. In this study, we estimate…

We address causal estimation in semi-competing risks settings, where a non-terminal event may be precluded by one or more terminal events. We define a principal-stratification causal estimand for treatment effects on the non-terminal event,…

Methodology · Statistics 2025-06-27 Karina Gelis-Cadena , Michael Daniels , Juned Siddique

Competing risks model time to first event and type of first event. An example from hospital epidemiology is the incidence of hospital-acquired infection, which has to account for hospital discharge of non-infected patients as a competing…

Methodology · Statistics 2013-04-09 Arthur Allignol , Jan Beyersmann , Thomas Gerds , Aurélien Latouche

Survivorship analysis allows to statistically analyze situations that can be modeled as waiting times to an event. These waiting times are characterized by the cumulative hazard rate, which can be estimated by the Nelson-Aalen estimator or…

Statistics Theory · Mathematics 2019-07-04 Niklas Hohmann

As cancer patient survival improves, late effects from treatment are becoming the next clinical challenge. Chemotherapy and radiotherapy, for example, potentially increase the risk of both morbidity and mortality from second malignancies…

Since the Great Financial Crisis (GFC), the use of stress tests as a tool for assessing the resilience of financial institutions to adverse financial and economic developments has increased significantly. One key part in such exercises is…

Econometrics · Economics 2022-02-08 Martin Guth

In applied time-to-event analysis, a flexible parametric approach is to model the hazard rate as a piecewise constant function of time. However, the change points and values of the piecewise constant hazard are usually unknown and need to…

Methodology · Statistics 2024-08-08 Manuel Rosenbaum , Jan Beyersmann , Michael Vogt

A typical situation in competing risks analysis is that the researcher is only interested in a subset of risks. This paper considers a depending competing risks model with the distribution of one risk being a parametric or semi-parametric…

Methodology · Statistics 2022-05-13 Simon M. S. Lo , Ralf A. Wilke

Many applications in medical statistics as well as in other fields can be described by transitions between multiple states (e.g. from health to disease) experienced by individuals over time. In this context, multi-state models are a popular…

Accelerated failure time (AFT) models are used widely in medical research, though to a much lesser extent than proportional hazards models. In an AFT model, the effect of covariates act to accelerate or decelerate the time to event of…

Methodology · Statistics 2020-06-15 Michael J. Crowther , Patrick Royston , Mark Clements

This paper addresses the task of modeling severity losses using segmentation when the data distribution does not fall into the usual regression frameworks. This situation is not uncommon in lines of business such as third-party liability…

Applications · Statistics 2021-11-29 Martin Bladt

Risk management is particularly concerned with extreme events, but analysing these events is often hindered by the scarcity of data, especially in a multivariate context. This data scarcity complicates risk management efforts. Various tools…

Methodology · Statistics 2026-01-15 Nisrine Madhar , Juliette Legrand , Maud Thomas

In epidemiological studies of time-to-event data, a quantity of interest to the clinician and the patient is the risk of an event given a covariate profile. However, methods relying on time matching or risk-set sampling (including Cox…

Methodology · Statistics 2020-09-23 Sahir Rai Bhatnagar , Maxime Turgeon , Jesse Islam , James A. Hanley , Olli Saarela

Aalen's linear hazard rate regression model is a useful and increasingly popular alternative to Cox' multiplicative hazard rate model. It postulates that an individual has hazard rate function $h(s)=z_1\alpha_1(s)+\cdots+z_r\alpha_r(s)$ in…

Methodology · Statistics 2026-03-04 Nils Lid Hjort , Emil Aas Stoltenberg

The hazard ratio from the Cox proportional hazards model is a ubiquitous summary of treatment effect. However, when hazards are non-proportional, the hazard ratio can lose a stable causal interpretation and become study-dependent because it…

Methodology · Statistics 2026-02-17 Xiang Meng , Lu Tian , Kenneth Kehl , Hajime Uno

A class of estimating functions is introduced for the regression parameter of the Cox proportional hazards model to allow unknown failure statuses on some study subjects. The consistency and asymptotic normality of the resulting estimators…

Statistics Theory · Mathematics 2007-08-22 Irene Gijbels , Danyu Lin , Zhiliang Ying

Cure rate models are mostly used to study data arising from cancer clinical trials. Its use in the context of infectious diseases has not been explored well. In 2008, Tournoud and Ecochard first proposed a mechanistic formulation of cure…

Methodology · Statistics 2024-01-10 Suvra Pal

In standardized educational testing, test items are reused in multiple test administrations. To ensure the validity of test scores, the psychometric properties of items should remain unchanged over time. In this paper, we consider the…

Applications · Statistics 2021-10-26 Yunxiao Chen , Yi-Hsuan Lee , Xiaoou Li

Credit risk stress testing has become an important risk management device which is used both by banks internally and by regulators. Stress testing is complex because it essentially means projecting a bank's full balance sheet conditional on…

Risk Management · Quantitative Finance 2024-01-18 Bernd Engelmann

Multi-state models provide an extension of the usual survival/event-history analysis setting. In the medical domain, multi-state models give the possibility of further investigating intermediate events such as relapse and remission. In this…

Methodology · Statistics 2021-06-24 D. Manevski , H. Putter , M. Pohar Perme , E. F. Bonneville , J. Schetelig , L. C. de Wreede