Results 61 to 70 of about 14,848,273 (189)

TIME-DEPENDENT COVARIATES IN THE COX PROPORTIONAL-HAZARDS REGRESSION MODEL [PDF]

Annual Review of Public Health, 1999
▪ Abstract  The Cox proportional-hazards regression model has achieved widespread use in the analysis of time-to-event data with censoring and covariates. The covariates may change their values over time. This article discusses the use of such time-dependent covariates, which offer additional opportunities but must be used with caution.
L D, Fisher, D Y, Lin
openaire   +2 more sources

Cox proportional hazard model.

, 2018
Cox proportional hazard model.
Sou Katayanagi (5349557), Shigeyuki Kawachi (5349554), Nobuyuki Koyama (2733205)   +2 more
core   +1 more source

Analysis of time to event outcomes in randomized controlled trials by generalized additive models. [PDF]

PLoS ONE, 2015
BACKGROUND:Randomized Controlled Trials almost invariably utilize the hazard ratio calculated with a Cox proportional hazard model as a treatment efficacy measure.
Christos Argyropoulos, Mark L Unruh
doaj   +1 more source

Time to recovery from visceral leishmaniasis and its predictors of mature visceral leishmaniasis patients admitted at Metema Hospital, Metema, Ethiopia

Scientific Reports
Visceral leishmaniasis (VL) is a neglected tropical disease that mostly affects the working-class and impoverished segments of society, having a significant negative effect on the economic development of the affected nation.
Habitamu Wudu, Chekol Alemu
doaj   +1 more source

Modelling non-life insurance in Sri Lanka using Cox Hazard Model and classification of risky customers

Ruhuna Journal of Science, 2020
Some of the major factors that help the decision-making process of an insurance company include Time of the first claim (TFC), claim Size and the frequency of claims.
W.A.R. De Mel , W.A.P.A. Chathurangani
doaj   +1 more source

Causal Mediation Analysis for the Cox Proportional Hazards Model with a Smooth Baseline Hazard Estimator

Journal of the Royal Statistical Society, Series C: Applied Statistics, 2016
An important problem within the social, behavioural and health sciences is how to partition an exposure effect (e.g. treatment or risk factor) among specific pathway effects and to quantify the importance of each pathway.
Wei Wang, Jeffrey M. Albert
semanticscholar   +1 more source

Application of Artificial Neural Network in Predicting the Survival Rate of Gastric Cancer Patients [PDF]

Iranian Journal of Public Health, 2011
"nBackground: The aim of this study was to predict the survival rate of Iranian gastric cancer patients using the Cox proportional hazard and artificial neural network models as well as comparing the ability of these approaches in predicting the ...
A Biglarian, E Hajizadeh, A Kazemnejad, MR Zali   +3 more
doaj   +2 more sources

Semiparametric estimation of a panel data proportional hazards model with fixed effects [PDF]

, 2002
This paper considers a panel duration model that has a proportional hazards specification with fixed effects. The paper shows how to estimate the baseline and integrated baseline hazard functions without assuming that they belong to known ...
Joel L. Horowitz, Horowitz, Joel, Horowitz, J., Lee, S., Lee, Sokbae, Sokbae (Simon) Lee   +5 more
core   +1 more source

COX PROPORTIONAL HAZARD AND EXPONENTIAL SURVIVAL ANALYSIS IN PATIENTS WITH END-STAGE CHRONIC KIDNEY FAILURE AT BOJONEGORO

Barekeng
End-stage chronic renal failure is a condition that requires long-term treatment such as haemodialysis and poses a serious threat to patient survival.
Nur Silviyah Rahmi, Achmad Rifai, M. Irfan Islami, Annisa Andra Azifa   +3 more
doaj   +1 more source

Deep learning approach for survival prediction for patients with synovial sarcoma

Tumor Biology, 2018
Synovial sarcoma is a rare disease with diverse progression characteristics. We developed a novel deep-learning-based prediction algorithm for survival rates of synovial sarcoma patients.
Ilkyu Han, June Hyuk Kim, Heeseol Park, Han-Soo Kim, Sung Wook Seo   +4 more
doaj   +1 more source