Choice of Estimators Based on Different Observations: Modified AIC and LCV Criteria

DOI10.1111/j.1467-9469.2010.00699.xzbMath1246.62215OpenAlexW1860348370MaRDI QIDQ2911666

Daniel Commenges, Bernoît Liquet

Publication date: 1 September 2012

Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9469.2010.00699.x

zbMATH Keywords

Kullback-Leibler risklikelihood cross-validationprognostic models

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02) Statistical aspects of information-theoretic topics (62B10)

Related Items (2)

Parametric inference for time-to-failure in multi-state semi-Markov models: A comparison of marginal and process approaches ⋮ Choice of Prognostic Estimators in Joint Models by Estimating Differences of Expected Conditional Kullback-Leibler Risks

Cites Work

• Estimating a difference of Kullback-Leibler risks using a normalized difference of AIC
• Selection between proportional and stratified hazards models based on expected log-likelihood
• Statistical models: conventional, penalized and hierarchical likelihood
• Estimating the dimension of a model
• Information criteria and statistical modeling.
• Using Auxiliary Variables for Improved Estimates of Survival Time
• The Focused Information Criterion
• Model Selection and Multimodel Inference
• Bias reduction of maximum likelihood estimates
• Some test statistics for use in multistate survival analysis
• Choice between Semi‐parametric Estimators of Markov and Non‐Markov Multi‐state Models from Coarsened Observations
• On Information and Sufficiency
• Statistical models based on counting processes

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