Bayesian model selection for group studies — Revisited

@article{Rigoux2014BayesianMS,
  title={Bayesian model selection for group studies — Revisited},
  author={L. Rigoux and K. Stephan and Karl J. Friston and J. Daunizeau},
  journal={NeuroImage},
  year={2014},
  volume={84},
  pages={971-985}
}
In this paper, we revisit the problem of Bayesian model selection (BMS) at the group level. We originally addressed this issue in Stephan et al. (2009), where models are treated as random effects that could differ between subjects, with an unknown population distribution. Here, we extend this work, by (i) introducing the Bayesian omnibus risk (BOR) as a measure of the statistical risk incurred when performing group BMS, (ii) highlighting the difference between random effects BMS and classical… Expand
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References

SHOWING 1-10 OF 41 REFERENCES
Bayesian model selection for group studies
  • 1,166
  • PDF
Comparing Families of Dynamic Causal Models
  • 600
  • PDF
Optimizing Experimental Design for Comparing Models of Brain Function
  • 47
  • PDF
Hierarchical Models
  • 68
  • PDF
Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
  • 4,909
  • PDF
Generalisability, Random Effects & Population Inference
  • 669
Comparing Dynamic Causal Models using AIC, BIC and Free Energy
  • W. Penny
  • Computer Science, Medicine
  • NeuroImage
  • 2012
  • 233
  • PDF
Dynamic causal modelling
  • 3,489
  • PDF
Dynamic causal modelling: A critical review of the biophysical and statistical foundations
  • 251
  • PDF
...
1
2
3
4
5
...