title: Administrative censoring in ecological analyses of autism and a Bayesian solution.
abstract: Widely cited ecological analyses of autism have reported associations with mercury emissions, with precipitation, and race at the level of counties or school districts. However, state educational agencies often suppress any low numerical autism counts before releasing data--a phenomenon known as "administrative censoring." Previous analyses did not describe appropriate methods for censored data analysis; common substitution or exclusion methods are known to introduce bias and produce artificially narrow confidence intervals. We apply a Bayesian censored random effects Poisson model to reanalyze associations between 2001 Toxic Release Inventory reported mercury emissions and 2000-2001 autism counts in Texas. Relative risk estimates for autism decreased from 4.44 (95% CI: 4.16, 4.74) per thousand lbs. of air mercury emissions using a naive zero-substitution approach to 1.42 (95% CI: 1.09, 1.78) using the Bayesian approach. Inadequate attention to censoring poses a serious threat to the validity of ecological analyses of autism and other health outcomes.
authors.affiliation: Program in Public Health, Department of Statistics, University of California, Irvine, 2241 Bren Hall, Irvine, CA 92697-1250, USA. sbartell@uci.edu
authors.forename: Scott M
authors.initials: SM
authors.lastname: Bartell
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Lewandowski
mesh_terms: D001321:Autistic Disorder / Q000139:chemically induced* / Q000453:epidemiology; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D003625:Data Collection; D003627:Data Interpretation, Statistical; D004781:Environmental Exposure; D005843:Geography; D006801:Humans; D008628:Mercury / Q000032:analysis / Q000633:toxicity*; D008954:Models, Biological; D015995:Prevalence; D018570:Risk Assessment; D012959:Socioeconomic Factors; D013781:Texas / Q000453:epidemiology; D013997:Time Factors
chemical_list: D008628:Mercury