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Probabilistic survival analysis models seek to estimate the distribution of the future occurrence (time) of an event given a set of covariates. In recent years, these models have preferred nonparametric specifications that avoid directly…

Machine Learning · Computer Science 2025-05-08 Deming Sheng , Ricardo Henao

Econometrics in general, and Panel Data methods in particular, are becoming crucial in Public Health Economics and Social Policy analysis. In this discussion paper, we employ a helpful approach of Feasible Generalized Least Squares (FGLS)…

Populations and Evolution · Quantitative Biology 2025-04-18 Luis-Felipe Arizmendi , Carlos De la Torre-Domingo , Erick W. Rengifo

Existing datasets available to address crucial problems, such as child mortality and family planning discontinuation in developing countries, are not ample for data-driven approaches. This is partly due to disjoint data collection efforts…

Machine Learning · Computer Science 2020-12-01 Girmaw Abebe Tadesse , Celia Cintas , Skyler Speakman , Komminist Weldemariam

A linear mixed-effects (LME) model is proposed for modelling and forecasting single and multi-population age-specific death rates (ASDRs). The innovative approach that we take in this study treats age, the interaction between gender and…

Applications · Statistics 2025-11-18 Reza Dastranj , Martin Kolar

Proportional hazards (PH), proportional odds (PO) and accelerated failure time (AFT) models have been widely used to deal with survival data in different fields of knowledge. Despite their popularity, such models are not suitable to handle…

Methodology · Statistics 2019-10-08 Fabio N. Demarqui , Vinicius D. Mayrink

The best known methods for estimating hazard rate functions in survival analysis models are either purely parametric or purely nonparametric. The parametric ones are sometimes too biased while the nonparametric ones are sometimes too…

Methodology · Statistics 2026-02-20 Nils Lid Hjort

In a cross-sectional study, adolescent and young adult females were asked to recall the time of menarche, if experienced. Some respondents recalled the date exactly, some recalled only the month or the year of the event, and some were…

Methodology · Statistics 2019-03-05 Sedigheh Mirzaei Salehabadi , Debasis Sengupta , Rahul Ghosal

We introduce a semi-parametric Bayesian model for survival analysis. The model is centred on a parametric baseline hazard, and uses a Gaussian process to model variations away from it nonparametrically, as well as dependence on covariates.…

Machine Learning · Statistics 2016-11-04 Tamara Fernández , Nicolás Rivera , Yee Whye Teh

Quantifying the number of deaths caused by the COVID-19 crisis has been an ongoing challenge for scientists, and no golden standard to do so has yet been established. We propose a principled approach to calculate age-adjusted yearly excess…

Applications · Statistics 2023-12-20 Giacomo De Nicola , Göran Kauermann

In Survival Analysis, the observed lifetimes often correspond to individuals for which the event occurs within a specific calendar time interval. With such interval sampling, the lifetimes are doubly truncated at values determined by the…

Methodology · Statistics 2021-03-29 Carla Moreira , Jacobo de Uña-Álvarez , Ana Cristina Santos , Henrique Barros

Bayesian nonparametric inferential procedures based on Markov chain Monte Carlo marginal methods typically yield point estimates in the form of posterior expectations. Though very useful and easy to implement in a variety of statistical…

Statistics Theory · Mathematics 2016-05-04 Julyan Arbel , Antonio Lijoi , Bernardo Nipoti

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

Probabilistic survival predictions from models trained with Maximum Likelihood Estimation (MLE) can have high, and sometimes unacceptably high variance. The field of meteorology, where the paradigm of maximizing sharpness subject to…

Machine Learning · Computer Science 2019-06-20 Anand Avati , Tony Duan , Sharon Zhou , Kenneth Jung , Nigam H. Shah , Andrew Ng

Undoubtedly, several countries worldwide endure to experience a continuous increase in life expectancy, extending the challenges of life actuaries and demographers in forecasting mortality. Although several stochastic mortality models have…

Applications · Statistics 2021-03-22 Mario Marino , Susanna Levantesi , Andrea Nigri

Competing risks occur in survival analysis when multiple causes of death are present. They play a prominent role in several domains extending beyond biostatistics to encompass epidemiology, actuarial sciences, and reliability theory. This…

Methodology · Statistics 2026-04-30 Claudio Del Sole , Antonio Lijoi , Igor Prünster

Analysis of child mortality is crucial as it pertains to the policy and programs of a country. The early assessment of patterns and trends in causes of child mortality help decision-makers assess needs, prioritize interventions, and monitor…

Computers and Society · Computer Science 2020-11-20 Asadullah Hill Galib , Nadia Nahar , B M Mainul Hossain

Mediation analysis for survival outcomes is challenging. Most existing methods quantify the treatment effect using the hazard ratio (HR) and attempt to decompose the HR into the direct effect of treatment plus an indirect, or mediated,…

In the evolving world, we require more additionally the young era to flourish and evolve into developed land. Most of the population all around the world are unaware of the complications involved in the routine they follow while they are…

Machine Learning · Computer Science 2023-12-08 S. Nandini , Sanjjushri Varshini R

In this paper we attempt to answer the following question: ``Is it possible to obtain reliable estimates for the prevalence of anemia rates in children under five years in the districts of Peru?'' Specifically, the interest of the present…

Applications · Statistics 2023-05-04 Anna Sikov , Jose Cerda-Hernandez

Treatment specific survival curves are an important tool to illustrate the treatment effect in studies with time-to-event outcomes. In non-randomized studies, unadjusted estimates can lead to biased depictions due to confounding. Multiple…

Methodology · Statistics 2023-04-25 Robin Denz , Renate Klaaßen-Mielke , Nina Timmesfeld