Results 1 to 10 of about 780,496 (328)

Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent [PDF]

Journal of Statistical Software, 2011
We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of l1 and l2 penalties (elastic net). Our algorithm fits via cyclical coordinate descent, and employs warm starts to find a solution along a ...
Noah Simon, Jerome Friedman, Trevor Hastie, Rob Tibshirani   +3 more
doaj   +3 more sources

Limitations of applying the COX proportional hazards model to glioma studies. [PDF]

J Transl Med
Xue J, Chen Y, Xue C, Yin Q, Lai R, Chen L, Wang M.   +6 more
europepmc   +4 more sources

On Cox proportional hazards model performance under different sampling schemes. [PDF]

PLoS One, 2023
Cox's proportional hazards model (PH) is an acceptable model for survival data analysis. This work investigates PH models' performance under different efficient sampling schemes for analyzing time to event data (survival data). We will compare a modified
Samawi H, Yu L, Yin J.
europepmc   +3 more sources

The Impact of Violation of the Proportional Hazards Assumption on the Calibration of the Cox Proportional Hazards Model. [PDF]

Stat Med
INTRODUCTION 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 ...
Austin PC, Giardiello D.
europepmc   +2 more sources

Quasi-linear Cox proportional hazards model with cross- L₁ penalty. [PDF]

BMC Med Res Methodol, 2020
Background To accurately predict the response to treatment, we need a stable and effective risk score that can be calculated from patient characteristics.
Omae K, Eguchi S.
europepmc   +2 more sources

Adjusting for bias introduced by instrumental variable estimation in the Cox Proportional Hazards Model [PDF]

Biostatistics, 2017
Instrumental variable (IV) methods are widely used for estimating average treatment effects in the presence of unmeasured confounders. However, the capability of existing IV procedures, and most notably the two-stage residual inclusion (2SRI) procedure ...
Goodney, Philip P., MacKenzie, Todd A., Martinez-Camblor, Pablo, O'Malley, A. James, Staiger, Douglas O.   +4 more
core   +2 more sources

Verticox+: vertically distributed Cox proportional hazards model with improved privacy guarantees. [PDF]

Complex Intell Systems
Federated learning allows us to run machine learning algorithms on decentralized data when data sharing is not permitted due to privacy concerns. Various models have been adapted to use in a federated setting.
van Daalen F, Smits D, Ippel L, Dekker A, Bermejo I.   +4 more
europepmc   +2 more sources

Limitations of using COX proportional hazards model in cardiovascular research. [PDF]

Cardiovasc Diabetol
The article by Zhao et al. titled “Associations of Triglyceride-Glucose (TyG) Index with Chest Pain Incidence and Mortality among the U.S. Population” provides valuable insights into the positive correlation between the TyG index and chest pain incidence,
Jiang N, Wu Y, Li C.
europepmc   +2 more sources

Regularization for Cox’s proportional hazards model with NP-dimensionality [PDF]

, 2011
High throughput genetic sequencing arrays with thousands of measurements per sample and a great amount of related censored clinical data have increased demanding need for better measurement specific model selection.
Jelena Bradić, Jianqing Fan, Jiancheng Jiang   +2 more
openalex   +3 more sources

Cox proportional hazards model with Bayesian neural network for survival prediction [PDF]

Sci Rep
Survival analysis plays a crucial aspect in medical research and other domains where understanding the time-to-events is paramount. In this study, we present a novel approach for estimating survival outcomes that combines Bayesian neural networks with ...
Faghiri F, Kohansal A.
europepmc   +2 more sources