title: Predictive inference, causal reasoning, and model assessment in nonparametric Bayesian analysis: a case study.
abstract: This paper continues our earlier analysis of a data set on acute ear infections in small children, presented in Andreev and Arjas (1998). The main goal here is to provide a method, based on the use of predictive distributions, for assessing the possible causal influence which the type of day care will have on the incidence of ear infections. A closely related technique is used for the assessment of the nonparametric Bayesian intensity model applied in the paper. Two graphical methods, supported by formal tests, are suggested for this purpose.
authors.affiliation: Rolf Nevanlinna Institute, University of Helsinki, Finland. elja.arjas@rni.helsinki.fi
authors.forename: E
authors.initials: E
authors.lastname: Arjas
authors.forename: A
authors.initials: A
authors.lastname: Andreev
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002656:Child Day Care Centers; D002675:Child, Preschool; D006801:Humans; D015994:Incidence; D007223:Infant; D015233:Models, Statistical; D010031:Otitis / Q000453:epidemiology*