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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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Cross-validation approaches for penalized Cox regression. [PDF]
Stat Methods Med ResCross-validation is the most common way of selecting tuning parameters in penalized regression, but its use in penalized Cox regression models has received relatively little attention in the literature. Due to its partial likelihood construction, carrying out cross-validation for Cox models is not straightforward, and there are several potential ...
Dai B, Breheny P.
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Cox Point Process Regression [PDF]
IEEE Transactions on Information Theory, 2022 Point processes in time have a wide range of applications that include the claims arrival process in insurance or the analysis of queues in operations research. Due to advances in technology, such samples of point processes are increasingly encountered. A key object of interest is the local intensity function.
Álvaro Gajardo, Hans-Georg Müller
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Cox regression with linked data [PDF]
Statistics in Medicine, 2023 Record linkage is increasingly used, especially in medical studies, to combine data from different databases that refer to the same entities. The linked data can bring analysts novel and valuable knowledge that is impossible to obtain from a single database.
Vo, Thanh Huan +6 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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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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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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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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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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