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Showing 1 to 20 of 320 for “"Survival analysis"”.
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Quantile regression and survival analysis
… and focus on two topics: quantile regression and survival analysis. Firstly, direct use of regression quantiles to construct confidence intervals and confidence bands for conditional quantiles and prediction intervals for future response variables under homoscedastic linear models and …
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Nonparametric Survival Analysis under Shape Restrictions
… model time-to- event data, particularly when the survival times of subjects under study are not exactly observed. One of the primary tasks in the analysis of survival data is to study the distribution of the event times of interest. In order to avoid strict assumptions associated with a parametric …
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Survival analysis for lung cancer patients
… usually has a poor prognosis, with a five years survival rate of only 21% according to the SEER Cancer Statistics Review, 1975-2017. With such a deadly disease, it is crucial to predict the survival likelihood of cancer patients. However, this is not an easy task due to the many factors affecting …
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Continuous Time Multi-state Models for Survival Analysis
The purpose of this paper is to discuss the survival analysis techniques for continuous time multi-state models. It explores homogeneous Markov models, homogeneous semi-Markov models, non-homogeneous Markov models, and general models. It also discusses the likelihoods, hazards, and probabilities …
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A Comparison of Discrete and Continuous Survival Analysis
There has been confusion in choosing a proper survival model between two popular survival models of discrete and continuous survival analysis. This study aimed to provide empirical outcomes of two survival models in educational contexts and suggest a guideline for researchers who should adopt a …
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The Impact of “Multiple Looks” when Performing Survival Analysis
<p>Survival analysis is a critical statistical method in healthcare to assess patient treatment effects and disease progression. Another critical area of statistical methodology in health care is the practice of adaptive designs. Adaptive designs allow for interim analyses to take place during a …
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Biologically Interpretable, Integrative Deep Learning for Cancer Survival Analysis
… biological processes associated to patients' survival time at the cellular and molecular level is critical not only for developing new treatments for patients but also for accurate survival prediction. However, highly nonlinear and high-dimension, low-sample size (HDLSS) data cause …
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Advancements on the Interface of Computer Experiments and Survival Analysis
Design and analysis of computer experiments is an area focusing on efficient data collection (e.g., space-filling designs), surrogate modeling (e.g., Gaussian process models), and uncertainty quantification. Survival analysis focuses on modeling the period of time until a certain event happens. …
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Introducción de variables macroeconómicas en modelos de scoring mediante survival analysis
… Scoring With Macroeconomic Variables Using Survival Analysis. En ese paper los autores aplican survival analysis incluyendo las típicas variables explicativas estáticas pero adicionando además variables macroeconómicas en la ventana en la que se sigue el comportamiento de las operaciones, ya …
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Joint Models for Longitudinal Analysis and Competing Risks in Survival Analysis
… Developing a joint longitudinal competing risks survival model in which previous wave disease status history is an additional time-varying covariate in the survival component, through the same linkage mechanism as in the baseline model. 3. Applying the same linkage mechanism as in the baseline …
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Comparison of Some Statistical and Machine Learning Models for Continuous Survival Analysis
… and machine learning models for continuous survival analysis utilizing two distinct datasets: time to first alcohol intake and North Carolina recidivism data. LassoCV was used to select variables for both datasets by encouraging limited coefficient estimates. Kaplan-Meier survival curves …
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Application of survival analysis modeling in water pipelines failure in Cape Town
… in Cape Town City have been modelled by using survival analysis techniques. Estimates of the Mean Cumulative Function (MCF) have been used to predict the failure rates of pipes in the network.
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Survival analysis of the modernized retirement system for the United States Marine Corps
… system and the Modernized Retirement System. The analysis utilizes Kaplan-Meier survival analysis for expected lengths of service and probit regression models to evaluate various retirement choices under the Modernized Retirement System. The results of the analysis indicate the U.S. Marine Corps …
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Federated Survival Analysis: Ensemble and Neural Methods for Distributed Time-to-Event Data
L'abstract è presente nell'allegato / the abstract is in the attachment
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