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Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 2020 Introduction The frequently used Cox regression applies two critical assumptions, which might not hold for all predictors. In this study, the results from a Cox regression model (CM) and a generalized Cox regression model (GCM) are compared. Methods Data
Jantje Goerdten +2 more
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Partial-linear single-index Cox regression models with multiple time-dependent covariates [PDF]
BMC Medical Research MethodologyBackground In cohort studies with time-to-event outcomes, covariates of interest often have values that change over time. The classical Cox regression model can handle time-dependent covariates but assumes linear effects on the log hazard function, which
Myeonggyun Lee +8 more
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Features of using Cox regression in various instrumental environments
Вестник университета, 2022 The presence of large amounts of data in information and analytical systems makes it necessary to study them using machine learning and artificial intelligence methods.
I. V. Kramarenko, L. A. Konstantinova
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Gene signature for prognosis in comparison of pancreatic cancer patients with diabetes and non-diabetes [PDF]
PeerJ, 2020 Background Pancreatic cancer (PC) has much weaker prognosis, which can be divided into diabetes and non-diabetes. PC patients with diabetes mellitus will have more opportunities for physical examination due to diabetes, while pancreatic cancer patients ...
Mingjun Yang +5 more
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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
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Sinusoidal Cox Regression—A Rare Cancer Example
Cancer Informatics, 2010 Evidence of an association between survival time and date of birth would suggest an etiologic role for a seasonally variable environmental exposure occurring within a narrow perinatal time period.
Jimmy Thomas Efird
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Image Based Data Mining Using Per-voxel Cox Regression
Frontiers in Oncology, 2020 Image Based Data Mining (IBDM) is a novel analysis technique allowing the interrogation of large amounts of routine radiotherapy data. Using this technique, unexpected correlations have been identified between dose close to the prostate and biochemical ...
Andrew Green +11 more
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Survival Analysis, Kaplan-Meier Curves, and Cox Regression: Basic Concepts
Indian Journal of Psychological Medicine, 2023 Survival analysis is used to analyze data from patients who are followed for different periods of time and in whom the outcome of interest, a dichotomous event, may or may not have occurred at the time the study is halted; data from all patients are used
Chittaranjan Andrade
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Cox regression survival analysis with compositional covariates: application to modelling mortality risk from 24-h physical activity patterns [PDF]
, 2020 Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular
Chastin, S.F.M. +4 more
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Factors associated with methadone treatment duration: a Cox regression analysis. [PDF]
PLoS ONE, 2015 This study examined retention rates and associated predictors of methadone maintenance treatment (MMT) duration among 128 newly admitted patients in Taiwan. A semi-structured questionnaire was used to obtain demographic and drug use history.
Chao-Kuang Lin +4 more
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