| Literature DB >> 28603397 |
Diba Khan1, Lauren M Rossen1, Brady Hamilton1, Erin Dienes2, Yulei He1, Rong Wei1.
Abstract
The objective of this analysis was to explore temporal and spatial variation in teen birth rates TBRs across counties in the USA, from 2003 to 2012, by using hierarchical Bayesian models. Prior examination of spatiotemporal variation in TBRs has been limited by the reliance on large-scale geographies such as states, because of the potential instability in TBRs at smaller geographical scales such as counties. We implemented hierarchical Bayesian models with space-time interaction terms and spatially structured and unstructured random effects to produce smoothed county level TBR estimates, allowing for examination of spatiotemporal patterns and trends in TBRs at a smaller geographic scale across the USA. The results may help to highlight US counties where TBRs are higher or lower and to inform efforts to reduce birth rates to adolescents in the USA further.Entities:
Keywords: Bayesian model; Convolution; Hierarchical Bayes method; Markov chain Monte Carlo methods; Small area estimation
Year: 2017 PMID: 28603397 PMCID: PMC5464734 DOI: 10.1111/rssa.12266
Source DB: PubMed Journal: J R Stat Soc Ser A Stat Soc ISSN: 0964-1998 Impact factor: 2.483