title: Statistical inference for a two-stage outcome-dependent sampling design with a continuous outcome.
abstract: The two-stage case-control design has been widely used in epidemiology studies for its cost-effectiveness and improvement of the study efficiency (White, 1982, American Journal of Epidemiology 115, 119-128; Breslow and Cain, 1988, Biometrika 75, 11-20). The evolution of modern biomedical studies has called for cost-effective designs with a continuous outcome and exposure variables. In this article, we propose a new two-stage outcome-dependent sampling (ODS) scheme with a continuous outcome variable, where both the first-stage data and the second-stage data are from ODS schemes. We develop a semiparametric empirical likelihood estimation for inference about the regression parameters in the proposed design. Simulation studies were conducted to investigate the small-sample behavior of the proposed estimator. We demonstrate that, for a given statistical power, the proposed design will require a substantially smaller sample size than the alternative designs. The proposed method is illustrated with an environmental health study conducted at National Institutes of Health.
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7420, USA. zhou@bios.unc.edu
authors.forename: Haibo
authors.initials: H
authors.lastname: Zhou
authors.forename: Rui
authors.initials: R
authors.lastname: Song
authors.forename: Yuanshan
authors.initials: Y
authors.lastname: Wu
authors.forename: Jing
authors.initials: J
authors.lastname: Qin
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D016022:Case-Control Studies; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods*