We propose innovative and cost-effective sampling designs that will enable the investigators to collect more informative samples at a fixed budget. We will also develop/evaluate new and efficient statistical methods that will reap the gains provided by these designs. User-friendly software and algorithms of the proposed designs/methods will be developed and disseminated. The proposed designs are generally multi-stage based and are of a biased sampling scheme where one observes the main exposure variable with a probability that depends on the outcome variable and auxiliary covariates. The proposed research is in response to the needs in design a more powerful study and these designs have been used in the current ongoing studies. These studies are collaborations the PI has with researchers at National Institute of Environmental Health Sciences to study the effects of environmental exposures on cancer and other diseases.
The specific aims i nclude: (1) Develop a FDS and two-stage FDS design for the Norwegian Mother and Child Cohort Study (MoBA) and evaluate an estimated empirical likelihood method. Data from MoBa study as well as the Cancer Risk in Uranium Miners Study will be analyzed;(2) Pro- pose a two-phase probability-dependent sampling (PDS) design for the Gulf Oil Spill Long-term Follow Up Study (GuLF) and evaluate a linear regression analysis and linear mixed model with PDS design. Data from GuLF Study will be analyzed with these methods. (3) Develop a two-stage Longitudinal outcome dependent sampling (LODS) sampling design for the Generation R Study with either a baseline response based sampling scheme or summation of all responses based sampling scheme. Data from Generation R Study as well as Collaborative Perinatal Project (CPP) will be analyzed with these methods;(4) Develop inference procedure for a continuous secondary response in a two-stage ODS design and a two-stage FDS design;Data from CPP Study, MoBa Study, and Uranium Miners Study will be analyzed;(5) Power study and optimal sample size allocation to achieve the maximum power for a given budget for studies with a two-stage FDS and two-phase PDS designs. The strengths and weaknesses of each proposed method will be critically examined via theoretical investigations and simulation studies. The developed software will be made available through publication and dedicated web page which will come with "User's Guide" as well as illustrative data examples on how to use them. Successful completion of the proposed research will have a significant impact on how future cost-effective biomedical studies to be conducted and how data from these studies be efficiently analyzed.
We propose innovative and cost-effective sampling designs that will enable the investigators to sample more informative samples at a fixed budget. We will also develop/evaluate new and efficient statistical methods that will reap the gains provided by these designs. User-friendly softwares will be developed and disseminated. These designs have been used in the current ongoing epidemiological studies to investigate effects of environmental exposures on cancer and other diseases. Successful completion of the proposed research will have a significant impact on how future biomedical studies to be conducted and how data from these studies be analyzed.
|Zhao, Yue; Herring, Amy H; Zhou, Haibo et al. (2014) A multiple imputation method for sensitivity analyses of time-to-event data with possibly informative censoring. J Biopharm Stat 24:229-53|
|Zhou, Haibo; Xu, Wangli; Zeng, Donglin et al. (2014) Semiparametric Inference for Data with a Continuous Outcome from a Two-Phase Probability Dependent Sampling Scheme. J R Stat Soc Series B Stat Methodol 76:197-215|
|Ding, Jieli; Zhou, Haibo; Liu, Yanyan et al. (2014) Estimating effect of environmental contaminants on women's subfecundity for the MoBa study data with an outcome-dependent sampling scheme. Biostatistics 15:636-50|