Improved AIC selection strategy for survival analysis

DOI10.1016/j.csda.2007.09.003zbMath1452.62087OpenAlexW2074463513WikidataQ36591875 ScholiaQ36591875MaRDI QIDQ1023584

Hua Liang, Guo Hua Zou

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2344147

zbMATH Keywords

survival analysisKullback-Leibler informationAICBIC

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Statistical aspects of information-theoretic topics (62B10) Reliability and life testing (62N05)

Related Items

Power piecewise exponential model for interval-censored data ⋮ An Akaike information criterion for multiple event mixture cure models ⋮ Bootstrap-based model selection criteria for beta regressions ⋮ Model selection criteria in beta regression with varying dispersion ⋮ Model selection and model averaging for analysis of truncated and censored data with measurement error ⋮ Visual research on the trustability of classical variable selection methods in Cox regression ⋮ Guided Censored Regression

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Estimating the dimension of a model
• Variable selection for Cox's proportional hazards model and frailty model
• Regression and time series model selection in small samples
• Further analysis of the data by Akaike's information criterion and the finite corrections
• Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
• Model Selection for Extended Quasi-Likelihood Models in Small Samples
• Bayesian Variable Selection Method for Censored Survival Data
• Bayesian Information Criterion for Censored Survival Models
• Some Comments on C P
• A new look at the statistical model identification