Strategies for inference robustness in focused modelling
DOI10.1080/02664760500251618zbMath1106.62002OpenAlexW2054542236MaRDI QIDQ3426401
E. C. Marshall, David J. Spiegelhalter
Publication date: 8 March 2007
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02664760500251618
predictionMarkov chain Monte Carloinfluence diagnosticsKullback-Leibler divergencemodel choicehierarchical modelsseasonal time seriesschool performanceinstitutional comparisonslung cancer death
Robustness and adaptive procedures (parametric inference) (62F35) Foundations and philosophical topics in statistics (62A01) Numerical analysis or methods applied to Markov chains (65C40)
Uses Software
Cites Work
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- Changes in utility as information
- Expected information as ecpected utility
- Bayesian marginal influence assessment
- Diagnostic Measures for Model Criticism
- Approximate methods for assessing influence and sensitivity in Bayesian analysis
- Sampling and Bayes' Inference in Scientific Modelling and Robustness
- Some Algebra and Geometry for Hierarchical Models, Applied to Diagnostics
- Statistical Methods for Profiling Providers of Medical Care: Issues and Applications
- Bayesian Inference for Prevalence in Longitudinal Two‐Phase Studies
- A Predictive View of the Detection and Characterization of Influential Observations in Regression Analysis
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