title: Hierarchical latency models for dose-time-response associations.
abstract: Exposure lagging and exposure-time window analysis are 2 widely used approaches to allow for induction and latency periods in analyses of exposure-disease associations. Exposure lagging implies a strong parametric assumption about the temporal evolution of the exposure-disease association. An exposure-time window analysis allows for a more flexible description of temporal variation in exposure effects but may result in unstable risk estimates that are sensitive to how windows are defined. The authors describe a hierarchical regression approach that combines time window analysis with a parametric latency model. They illustrate this approach using data from 2 occupational cohort studies: studies of lung cancer mortality among 1) asbestos textile workers and 2) uranium miners. For each cohort, an exposure-time window analysis was compared with a hierarchical regression analysis with shrinkage toward a simpler, second-stage parametric latency model. In each cohort analysis, there is substantial stability gained in time window-specific estimates of association by using a hierarchical regression approach. The proposed hierarchical regression model couples a time window analysis with a parametric latency model; this approach provides a way to stabilize risk estimates derived from a time window analysis and a way to reduce bias arising from misspecification of a parametric latency model.
authors.affiliation: Department of Epidemiology, School of Public Health, University of North Carolina, Chapel Hill, NC 27599-7435, USA. david.richardson@unc.edu
authors.forename: David B
authors.initials: DB
authors.lastname: Richardson
authors.forename: Richard F
authors.initials: RF
authors.lastname: MacLehose
authors.forename: Bryan
authors.initials: B
authors.lastname: Langholz
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Cole
mesh_terms: D001194:Asbestos / Q000009:adverse effects; D004305:Dose-Response Relationship, Drug; D006801:Humans; D008175:Lung Neoplasms / Q000139:chemically induced*; D008906:Mining; D015233:Models, Statistical; D008962:Models, Theoretical; D016273:Occupational Exposure / Q000009:adverse effects* / Q000706:statistics & numerical data; D011886:Radon / Q000009:adverse effects; D012044:Regression Analysis; D018570:Risk Assessment; D013783:Textile Industry; D013997:Time Factors; D014501:Uranium / Q000009:adverse effects
chemical_list: D001194:Asbestos; D014501:Uranium; D011886:Radon