Results 1 to 10 of about 203,116 (160)
The impact of violation of the proportional hazards assumption on the discrimination of the Cox proportional hazards model [PDF]
Diagnostic and Prognostic ResearchBackground The 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.
Peter C. Austin, Daniele Giardiello
doaj +4 more sources
Epidemiology, Biostatistics and Public HealthINTRODUCTION 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 ...
Peter Austin, Daniele Giardiello
doaj +6 more sources
A Bayesian network interpretation of the Cox's proportional hazard model
International Journal of Approximate Reasoning, 2018 Cox's proportional hazards (CPH) model is quite likely the most popular modeling technique in survival analysis. While the CPH model is able to represent a relationship between a collection of risks and their common effect, Bayesian networks have become an attractive alternative with an increased modeling power and far broader applications.
Marek J Drużdżel, Jidapa Kraisangka
exaly +5 more sources
Generating survival times to simulate Cox proportional hazards models [PDF]
Statistics in Medicine, 2005 Abstract Simulation studies present an important statistical tool to investigate the performance, properties and adequacy of statistical models in pre‐specified situations. One of the most important statistical models in medical research is the proportional hazards model of Cox. In this paper, techniques to generate survival times for
Thomas Augustin, Ralf Bender
exaly +4 more sources
Estimation in a Cox Proportional Hazards Cure Model [PDF]
Biometrics, 2000 Summary.Some failure time data come from a population that consists of some subjects who are susceptible to and others who are nonsusceptible to the event of interest. The data typically have heavy censoring at the end of the follow‐up period, and a standard survival analysis would not always be appropriate.
Sy, Judy P., Taylor, Jeremy M. G.
openaire +4 more sources
Modeling of Distance Learners’ Retention Using Mixed-Model on Non-Proportional Hazard
Journal of Open, Flexible and Distance Learning, 2023 Universitas Terbuka is a public university in Indonesia that implements an open-distance education system. The quality and success of higher education in Indonesia are indicated by the gross enrolment rate (GER).
Dewi Juliah Ratnaningsih
doaj +3 more sources
The Optimal Machine Learning-Based Missing Data Imputation for the Cox Proportional Hazard Model
Frontiers in Public Health, 2021 An adequate imputation of missing data would significantly preserve the statistical power and avoid erroneous conclusions. In the era of big data, machine learning is a great tool to infer the missing values.
Chao-Yu Guo +4 more
doaj +1 more source
MethodsX, 2023 The instrumental variable (IV) method with a Cox proportional hazard (PH) model has been used to evaluate treatment effects in epidemiological studies involving survival data. The effectiveness of the IV methods in these circumstances has yet to be fully
Md. Jamal Uddin +2 more
doaj +1 more source
Analysis of The Debtor's Endurance using Cox Regression Semiparametric Method
Jurnal Ilmu Keuangan dan Perbankan, 2022 The aim of this research was conducted to determine the factors that influence the resilience of car loan debtors in an area. The research method used is semiparametric Cox regression on secondary data, WAREHOUSE consisting of the customer profile ...
Vitri Aprilla Handayani* +3 more
doaj +1 more source
A Federated Cox Model with Non-Proportional Hazards
CoRR, 2022 Recent research has shown the potential for neural networks to improve upon classical survival models such as the Cox model, which is widely used in clinical practice. Neural networks, however, typically rely on data that are centrally available, whereas healthcare data are frequently held in secure silos.
Dekai Zhang +2 more
openaire +2 more sources