Biostatistics, 2013 Frailty models account for the clustering present in event time data. A proportional hazards model with shared frailties expresses the hazard for each subject. Often a one-parameter gamma distribution is assumed for the frailties.
Candida Geerdens +2 more
semanticscholar +1 more source
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
doaj +1 more source
The hazard ratio is interpretable as an odds or a probability under the assumption of proportional hazards [PDF]
arXiv, 2021 Three statistical studies, all published between 2004 and 2008 but without referring to one another, assert a useful equivalence involving the hazard ratio, a parameter estimated for time to event data by the frequently used proportional hazards model.
arxiv
BMC Medical Research Methodology, 2018 Background Multidrug-resistant tuberculosis (MDR-TB) cohorts often lack long-term survival data, and are summarized instead by initial treatment outcomes.
Meredith B. Brooks +5 more
doaj +1 more source
Analysis of competing risks in the CoxPH model for progressive censorship with binomial removal [PDF]
Jorjani Biomedicine Journal, 2023 Background: In medical research and survival analysis, it is common for an individual or item's failure to be attributable to multiple causes, also known as competing risks.
Ahmad Pourdarvish +3 more
doaj
Comparison of radiomic feature aggregation methods for patients with multiple tumors
Scientific Reports, 2021 Radiomic feature analysis has been shown to be effective at analyzing diagnostic images to model cancer outcomes. It has not yet been established how to best combine radiomic features in cancer patients with multifocal tumors.
Enoch Chang +7 more
doaj +1 more source
Simulating Survival Data Using the simsurv R Package
Journal of Statistical Software, 2021 The simsurv R package allows users to simulate survival (i.e., time-to-event) data from standard parametric distributions (exponential, Weibull, and Gompertz), two-component mixture distributions, or a user-defined hazard function.
Samuel L. Brilleman +3 more
doaj +1 more source
Stochastic Comparisons of Second-Order Statistics from Dependent and Heterogenous Modified Proportional Hazard Rate Observations [PDF]
arXiv, 2022 In this manuscript, we study stochastic comparisons of the second-order statistics from dependent or independent observations with modified proportional hazard rates models. First, we establish the usual stochastic order of the second-order statistics from dependent and heterogeneous observations.
arxiv
Likelihood-based Instrumental Variable Methods for Cox Proportional Hazard Models [PDF]
arXiv, 2022 In biometrics and related fields, the Cox proportional hazards model are widely used to analyze with covariate adjustment. However, when some covariates are not observed, an unbiased estimator usually cannot be obtained. Even if there are some unmeasured covariates, instrumental variable methods can be applied under some assumptions.
arxiv
A flexible alternative to the Cox proportional hazards model for assessing the prognostic accuracy of hospice patient survival. [PDF]
PLoS ONE, 2012 Prognostic models are often used to estimate the length of patient survival. The Cox proportional hazards model has traditionally been applied to assess the accuracy of prognostic models.
Branko Miladinovic +5 more
doaj +1 more source