A comparison of time to event analysis methods, using weight status and breast cancer as a case study
Abstract Survival analysis with cohort study data has been traditionally performed using Cox proportional hazards models. Random survival forests (RSFs), a machine learning method, now present an alternative method. Using the UK Women’s Cohort Study (n = 34,493) we evaluate two methods: a Cox model...
Enregistré dans:
Auteurs principaux: | Georgios Aivaliotis, Jan Palczewski, Rebecca Atkinson, Janet E. Cade, Michelle A. Morris |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/bdff11217d9a40ce95f2803a85af8a03 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Weigh-in time affects hydration status and acute weight gain in combat sports: A comparison of judo and wrestling
par: Bayram Ceylan, et autres
Publié: (2021) -
The anticipation of events in time
par: Matthias Grabenhorst, et autres
Publié: (2019) -
Pregnancy weight gain and childhood body weight: a within-family comparison.
par: David S Ludwig, et autres
Publié: (2013) -
HER2/neu Status in Breast Cancer Specimens: Comparison of Immunohistochemistry (IHC) and Fluorescence in situ Hybridization (FISH) Methods
par: Saglican,Yesim, et autres
Publié: (2015) -
An electrostatics method for converting a time-series into a weighted complex network
par: Dimitrios Tsiotas, et autres
Publié: (2021)