Results 31 to 40 of about 784,292 (229)
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
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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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Bayesian semiparametric inference for multivariate doubly-interval-censored data [PDF]
, 2010 Based on a data set obtained in a dental longitudinal study, conducted in Flanders (Belgium), the joint time to caries distribution of permanent first molars was modeled as a function of covariates.
De Iorio, Maria +3 more
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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
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
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
, 2018 The Cox model, which remains as the first choice in analyzing time-to-event data even for large datasets, relies on the proportional hazards assumption. When the data size exceeds the computer memory, the standard statistics for testing the proportional ...
Schifano, Elizabeth D. +3 more
core +1 more source
Regularization for Cox's proportional hazards model with NP-dimensionality
, 2012 High throughput genetic sequencing arrays with thousands of measurements per sample and a great amount of related censored clinical data have increased demanding need for better measurement specific model selection.
Bradic, Jelena +2 more
core +1 more source
Partial Orders with Respect to Continuous Covariates and Tests for the Proportional Hazards Model [PDF]
, 2008 Several omnibus tests of the proportional hazards assumption have been proposed in the literature. In the two-sample case, tests have also been developed against ordered alternatives like monotone hazard ratio and monotone ratio of cumulative hazards ...
Bhattacharjee, Arnab
core +3 more sources
A mixed model approach for structured hazard regression [PDF]
, 2004 The classical Cox proportional hazards model is a benchmark approach to analyze continuous survival times in the presence of covariate information. In a number of applications, there is a need to relax one or more of its inherent assumptions, such as ...
Fahrmeir, Ludwig, Kneib, Thomas
core +2 more sources