title: Two error components model for measurement error: application to radon in homes.
abstract: In this paper, a simple model for analysing variability in radon concentrations in homes is tested. The approach used here involves two error components, representing additive and multiplicative errors, together with variation between-houses. We use a Bayesian approach for our analysis and apply this model to two datasets of repeat radon measurements in homes; one based on 3-month long measurements for which the original measurements were close to the current UK Radon Action Level (200 Bq m(-3)), and the other based on 6-month measurement data (from regional and national surveys), for which the original measurements cover a wide range of radon concentrations, down to very low levels. The model with two error components provides a better fit to these datasets than does a model based on solely multiplicative errors.
authors.affiliation: Health Protection Agency, CRCE (Centre for Radiation, Chemical and Environmental Hazards), Chilton, Oxon OX11 0RQ, UK. nezahat.hunter@hpa.org.uk
authors.forename: Nezahat
authors.initials: N
authors.lastname: Hunter
authors.forename: Colin R
authors.initials: CR
authors.lastname: Muirhead
authors.forename: Jon C H
authors.initials: JC
authors.lastname: Miles
mesh_terms: D016902:Air Pollution, Indoor / Q000032:analysis*; D001499:Bayes Theorem; D006798:Housing; D006801:Humans; D015233:Models, Statistical; D011834:Radiation Monitoring / Q000379:methods* / Q000706:statistics & numerical data; D011886:Radon / Q000032:analysis*; D012107:Research Design / Q000706:statistics & numerical data
chemical_list: D011886:Radon