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Deviance information criteria for missing data models. (English) Zbl 1331.62329
Summary: The deviance information criterion (DIC) introduced by D. J. Spiegelhalter et al. [J. R. Stat. Soc., Ser. B, Stat. Methodol. 64, No. 4, 583–639 (2002; Zbl 1067.62010)] for model assessment and model comparison is directly inspired by linear and generalised linear models, but it is open to different possible variations in the setting of missing data models, depending in particular on whether or not the missing variables are treated as parameters. In this paper, we reassess the criterion for such models and compare different DIC constructions, testing the behaviour of these various extensions in the cases of mixtures of distributions and random effect models.

MSC:
62J05 Linear regression; mixed models
62J12 Generalized linear models (logistic models)
62C10 Bayesian problems; characterization of Bayes procedures
62F15 Bayesian inference
62B10 Statistical aspects of information-theoretic topics
Software:
WinBUGS
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