Results 31 to 40 of about 1,576,634 (357)
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
BMC Musculoskeletal Disorders, 2021 Background Survival analysis and effect of covariates on survival time is a central research interest. Cox proportional hazards regression remains as a gold standard in the survival analysis. The Cox model relies on the assumption of proportional hazards
I. Kuitunen +4 more
semanticscholar +1 more source
Biometrics, 2016 The proportional hazards model (PH) is currently the most popular regression model for analyzing time‐to‐event data. Despite its popularity, the analysis of interval‐censored data under the PH model can be challenging using many available techniques ...
Lianming Wang +3 more
semanticscholar +1 more source
Comparison of methods for estimating the attributable risk in the context of survival analysis
BMC Medical Research Methodology, 2017 Background The attributable risk (AR) measures the proportion of disease cases that can be attributed to an exposure in the population. Several definitions and estimation methods have been proposed for survival data.
Malamine Gassama +3 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
Trend-constrained corrected score for proportional hazards model with covariate measurement error
Contemporary Clinical Trials Communications, 2015 In many medical research studies, survival time is typically the primary outcome of interest. The Cox proportional hazards model is the most popular method to investigate the relationship between covariates and possibly right-censored survival time ...
Ming Zhu, Yijian Huang
doaj +1 more source
The importance of censoring in competing risks analysis of the subdistribution hazard
BMC Medical Research Methodology, 2017 Background The analysis of time-to-event data can be complicated by competing risks, which are events that alter the probability of, or completely preclude the occurrence of an event of interest.
Mark W. Donoghoe, Val Gebski
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
E-Jurnal Matematika, 2013 Survival analysis is a statistical method that accommodates the collection of censored data. One of popular method in survival analysis is the Cox Proportional Hazard Regression.
I GEDE ARI SUDANA +2 more
doaj +1 more source