Information methods for model selection in linear mixed effects models with application to HCV data

@article{Dimova2011InformationMF,
  title={Information methods for model selection in linear mixed effects models with application to HCV data},
  author={Rositsa Dimova and Marianthi Markatou and Andrew H. Talal},
  journal={Computational Statistics & Data Analysis},
  year={2011},
  volume={55},
  pages={2677-2697}
}
In this paper, we derive a small sample Akaike information criterion, based on the maximized loglikelihood, and a small sample information criterion based on the maximized restricted loglikelihood in the linear mixed effects model when the covariance matrix of the random effects is known. Small sample corrected information criteria are proposed for a special case of linear mixed effects models, the balanced random-coefficient model, without assuming the random coefficients covariance matrix to… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 41 REFERENCES

Information theory and an extension of the maximum likelihood principle in: B.N

H. Akaike
  • 1973
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

Longitudinal data model selection

  • Computational Statistics & Data Analysis
  • 2006
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL