Results 11 to 20 of about 871,313 (293)

Partial-linear single-index Cox regression models with multiple time-dependent covariates [PDF]

BMC Medical Research Methodology
Background 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, Andrea B. Troxel, Sophia Kwon, George Crowley, Theresa Schwartz, Rachel Zeig-Owens, David J. Prezant, Anna Nolan, Mengling Liu   +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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Assumption-Lean Cox Regression

Journal of the American Statistical Association, 2022
Inference for the conditional association between an exposure and a time-to-event endpoint, given covariates, is routinely based on partial likelihood estimators for hazard ratios indexing Cox proportional hazards models. This approach is flexible and makes testing straightforward, but is nonetheless not entirely satisfactory.
Stijn Vansteelandt, Oliver Dukes, Kelly Van Lancker, Torben Martinussen   +3 more
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Cox regression model under dependent truncation [PDF]

Biometrics, 2021
AbstractTruncation is a statistical phenomenon that occurs in many time‐to‐event studies. For example, autopsy‐confirmed studies of neurodegenerative diseases are subject to an inherent left and right truncation, also known as double truncation. When the goal is to study the effect of risk factors on survival, the standard Cox regression model cannot ...
Lior Rennert, Sharon X. Xie
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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, Boni Song, Juxiang Liu, Zhitong Bing, Yonggang Wang, Linmiao Yu   +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*, Widya Reza, Andini Setyo Anggraeni, Garry Rusmadi   +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, Andrew Green, Eliana Vasquez Osorio, Eliana Vasquez Osorio, Marianne C. Aznar, Marianne C. Aznar, Marianne C. Aznar, Alan McWilliam, Alan McWilliam, Marcel van Herk, Marcel van Herk, Marcel van Herk   +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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Survival Analysis II: Cox Regression [PDF]

Nephron Clinical Practice, 2011
In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the Cox regression method, and to provide some guidance ...
Stel, V.S., Dekker, F.W., Tripepi, G., Zoccali, C., Jager, K.J.   +4 more
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