Results 1 to 10 of about 829,002 (272)

An exponential bound for Cox regression [PDF]

Statistics & Probability Letters, 2012
We present an asymptotic exponential bound for the deviation of the survival function estimator of the Cox model. We show that the bound holds even when the proportional hazards assumption does not hold.
Goldberg, Y., Kosorok, M. R.
openaire   +4 more sources

Factors associated with survival of tuberculosis patients in Southeast Iran: comparison of stepwise cox regression, survival tree, and random survival forest. [PDF]

BMC Public Health
Sharafi M, Narouee S, Rasoulizadeh F, TalebiMoghaddam M, Dadgar J, Khaleghi M, Zakeri A, Baeradeh N.   +7 more
europepmc   +3 more sources

Study on risk factors of Montgomery T-tube extraction in patients with post-tracheotomy tracheal stenosis based on Cox regression analysis. [PDF]

BMC Pulm Med
Liu X, Li L, Nan F, Liu J, Zou H, Zhang N, Wang H.   +6 more
europepmc   +3 more sources

Prognostic factors and overall survival for second primary malignancies in myelodysplastic syndromes: a Cox regression coupled with competing risk model based on Surveillance, Epidemiology, and End Results (SEER) database. [PDF]

Transl Cancer Res
Li H, Li Q, Ge J, Zhu P, Zhou Z, Zhe N.
europepmc   +2 more sources

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
openaire   +3 more sources

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
openaire   +3 more sources

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., Dall, P.M., Hron, K., McGregor, D.E., Palarea-Albaladejo, J.   +4 more
core   +1 more source

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
openaire   +4 more sources

Demographic and clinical predictors of treatment outcomes in invasive lobular carcinoma breast cancer: insights from Cox regression analysis. [PDF]

Discov Oncol
Kaindal S, Venkataramana B.
europepmc   +3 more sources

Cox regression with linked data

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, Garès, Valérie, Zhang, Li-Chun, Happe, André, Oger, Emmanuel, Paquelet, Stéphane, Chauvet, Guillaume   +6 more
openaire   +5 more sources