The main objective of this grant application is to develop and evaluate improved statistical methods for the design and analysis of epidemiologic studies conducted with an outcome-dependent sampling (ODS) scheme. Sampling strategies that lead to a more cost-effective design in a given setting will be investigated. The proposed methods are particularly useful for cancer and environmental research because exposure misclassification and expensive exposure assessment are frequent challenges. The proposal consists of four projects. The first project deals with a onestage ODS design with a continuous outcome variable. In this project, two methods for making inferences about regression parameters will be studied: a semiparametric likelihood approach for observed ODS sample, and a pseudo-likelihood approach for further improving efficiency when the values of the outcome variable are known for the underlying cohort. The second project considers a new inference procedure for case-control studies in the presence of surrogate and missing/mismeasured exposure information. The third project concerns a new semiparametric likelihood based inference procedure that improves study efficiency by combining a superior measurement of exposure from the ODS sample and an inferior measurement from the underlying cohort population. The fourth project considers a new semiparametric likelihood based inference procedure for a two-stage ODS design with a continuous outcome variable. This design uses the information on surrogate or confounding covariates for subjects in stage one, to target sampling from certain subpopulations in the second stage of sampling. The strengths and weaknesses of each proposed method will be critically examined via theoretical investigations and simulation studies. Comparisons with existing methods will be conducted. Related software will be developed. Data sets from ongoing epidemiologic studies on the effects of environmental and nutritional exposures, and on cancer and cardiovascular disease will be analyzed using the methods developed. These include the Magnetic Fields and Breast Cancer Risk Study, the Collaborative Perinatal Project, the Cancer Risk in Uranium Miners Study, the Atherosclerosis Risk in Communities Study, the Pregnancy, Infection, and Nutrition Study, and the Epidemiology of Exertion, Stress, and Preterm Delivery Study.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Special Emphasis Panel (ZRG1-STA (01))
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University of North Carolina Chapel Hill
Biostatistics & Other Math Sci
Schools of Public Health
Chapel Hill
United States
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Xu, Wangli; Zhou, Haibo (2012) Mixed effect regression analysis for a cluster-based two-stage outcome-auxiliary-dependent sampling design with a continuous outcome. Biostatistics 13:650-64
Liu, Yanyan; Yuan, Zhongshang; Cai, Jianwen et al. (2012) Marginal hazard regression for correlated failure time data with auxiliary covariates. Lifetime Data Anal 18:116-38
Zhou, Haibo; You, Jinhong; Qin, Guoyou et al. (2011) A Partially Linear Regression Model for Data from an Outcome-Dependent Sampling Design. J R Stat Soc Ser C Appl Stat 60:559-574
Zhou, Haibo; Qin, Guoyou; Longnecker, Matthew P (2011) A partial linear model in the outcome-dependent sampling setting to evaluate the effect of prenatal PCB exposure on cognitive function in children. Biometrics 67:876-85
Zhou, Haibo; Wu, Yuanshan; Liu, Yanyan et al. (2011) Semiparametric inference for a 2-stage outcome-auxiliary-dependent sampling design with continuous outcome. Biostatistics 12:521-34
Qin, Guoyou; Zhou, Haibo (2011) Partial linear inference for a 2-stage outcome-dependent sampling design with a continuous outcome. Biostatistics 12:506-20
Zhou, Haibo; Zou, Baiming; Hazucha, Milan et al. (2011) Nasal nitric oxide and lifestyle exposure to tobacco smoke. Ann Otol Rhinol Laryngol 120:455-9
Zhou, Haibo; Song, Rui; Wu, Yuanshan et al. (2011) Statistical inference for a two-stage outcome-dependent sampling design with a continuous outcome. Biometrics 67:194-202
Liu, Yanyan; Wu, Yuanshan; Cai, Jianwen et al. (2010) Additive-multiplicative rates model for recurrent events. Lifetime Data Anal 16:353-73
Carson, Johnny L; Lu, Tsui-Shan; Brighton, Luisa et al. (2010) Phenotypic and physiologic variability in nasal epithelium cultured from smokers and non-smokers exposed to secondhand tobacco smoke. In Vitro Cell Dev Biol Anim 46:606-12

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