The impact of violation of the proportional hazards assumption on the discrimination of the Cox proportional hazards model. [PDF]
Diagn Progn ResThe Cox proportional hazards regression model is frequently used to estimate an individual's probability of experiencing an outcome within a specified prediction horizon. A key assumption of this model is that of proportional hazards. An important component of validating a prediction model is assessing its discrimination.
Austin PC, Giardiello D.
europepmc +4 more sources
The Impact of Violation of the Proportional Hazards Assumption on the Calibration of the Cox Proportional Hazards Model. [PDF]
Stat MedINTRODUCTION The Cox proportional hazards regression model is frequently used to develop clinical prediction models for time-to-event outcomes, allowing clinicians to estimate an individual’s risk of experiencing the outcome within specified time horizons (e.g., estimate an individual’s 10-year risk of death) [1].
Austin PC, Giardiello D.
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Why use methods that require proportional hazards? [PDF]
American Journal of EpidemiologyMats Julius Stensrud, , Hernán MIGUEL A
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Generalized Proportional Reversed Hazards Model [PDF]
The Egyptian Statistical Journal, 2004 Inthis paper, we propose to generalized proportional reversed hazards model by Tsx*,t=[Ts,(X, t)]a, where Tsx*,tis baseline distribution func- tion and a is a positive real number.
M. Kayid, I. Elbatal
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Regression Models for Lifetime Data: An Overview
Stats, 2022 Two methods dominate the regression analysis of time-to-event data: the accelerated failure time model and the proportional hazards model. Broadly speaking, these predominate in reliability modelling and biomedical applications, respectively.
Chrys Caroni
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On Cox proportional hazards model performance under different sampling schemes.
PLoS ONE, 2023 Cox's proportional hazards model (PH) is an acceptable model for survival data analysis. This work investigates PH models' performance under different efficient sampling schemes for analyzing time to event data (survival data). We will compare a modified
Hani Samawi, Lili Yu, JingJing Yin
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Interval-Censored Regression with Non-Proportional Hazards with Applications
Stats, 2023 Proportional hazards models and, in some situations, accelerated failure time models, are not suitable for analyzing data when the failure ratio between two individuals is not constant. We present a Weibull accelerated failure time model with covariables
Fábio Prataviera +4 more
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Pain and mortality among older adults in Korea [PDF]
Epidemiology and Health, 2021 OBJECTIVES With the increasing elderly population with chronic disease, understanding pain and designing appropriate policy interventions to it have become crucial.
Chiil Song, Wankyo Chung
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A New Family of Distributions Based on Proportional Hazards
Mathematics, 2022 In this article, we introduce a new family of symmetric-asymmetric distributions based on skew distributions and on the family of order statistics with proportional hazards.
Guillermo Martínez-Flórez +4 more
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Nonparametric Sieve Maximum Likelihood Estimation of Semi-Competing Risks Data
Mathematics, 2022 In biomedical studies involving time-to-event data, a subject may experience distinct types of events. We consider the problem of estimating the transition functions for a semi-competing risks model under illness-death model framework.
Xifen Huang, Jinfeng Xu
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