Group and within-group variable selection for competing risks data
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Publication:725412
DOI10.1007/s10985-017-9400-9zbMath1468.62370OpenAlexW2744006520WikidataQ38639634 ScholiaQ38639634MaRDI QIDQ725412
Anjishnu Banerjee, Natasha Sahr, Kwang Woo Ahn, Soyoung Kim
Publication date: 1 August 2018
Published in: Lifetime Data Analysis (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc5797529
Asymptotic properties of parametric estimators (62F12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)
Related Items (4)
Optimal treatment regimes for competing risk data using doubly robust outcome weighted learning with bi-level variable selection ⋮ Scalable Algorithms for Large Competing Risks Data ⋮ Group selection via adjusted weighted least absolute deviation regression ⋮ A general adaptive ridge regression method for generalized linear models: an iterative re-weighting approach
Uses Software
Cites Work
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- A Proportional Hazards Model for the Subdistribution of a Competing Risk
- Variable selection for censored quantile regression
- Model Selection and Estimation in Regression with Grouped Variables
- Variable selection for multivariate failure time data
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