Acute middle ear infection in small children: a Bayesian analysis using multiple time scales.
The study is based on a sample of 965 children living in Oulu region (Finland), who were monitored for acute middle ear infections from birth to the age of two years. We introduce a nonparametrically defined intensity model for ear infections, which involves both fixed and time dependent covariates, such as calendar time, current age, length of breast-feeding time until present, or current type of day care. Unmeasured heterogeneity, which manifests itself in frequent infections in some children and rare in others and which cannot be explained in terms of the known covariates, is modelled by using individual frailty parameters. A Bayesian approach is proposed to solve the inferential problem. The numerical work is carried out by Monte Carlo integration (Metropolis-Hastings algorithm).
Andreev
A
A
Department of Mathematical Sciences, University of Oulu, Finland.
Arjas
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E
D000208:Acute Disease; D000465:Algorithms; D001499:Bayes Theorem; D002675:Child, Preschool; D015331:Cohort Studies; D005260:Female; D005387:Finland / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D016013:Likelihood Functions; D008297:Male; D008390:Markov Chains; D008432:Mathematical Computing; D015233:Models, Statistical; D010033:Otitis Media / Q000453:epidemiology*; D011446:Prospective Studies; D012307:Risk Factors