This program project is ambitious, involving investigators, research projects, and resources across three insti- tutions: Duke University, North Carolina State University, and the University of North Carolina at Chapel Hill. Successful coordination of the investigators into an effective and productive team, integration of their research efforts, and management of program resources and finances requires a thoughtful administrative structure. Core A, the Administrative Core, is responsible for overseeing these functions and for orchestrating program dissemination and outreach efforts. Core A will provide program project administrative leadership through an Executive Committee comprising the three PD/PIs from each institution and will provide scientific leadership and guidance through a Steering Committee consisting of the Executive, three co-PD/PIs from each institution, and additional project and core leaders. The core will coordinate an External Advisory Committee of experts, which will meet with the Steering Committee and other project investigators at least once a year and provide con- structive feedback on the goals and progress of the program. The core will also oversee mechanisms to foster interdisciplinary and interinstitutional collaboration on research, including focused research groups organized around cross-cutting research themes of interest to more than one project. Core A will also be responsible for oversight of dissemination of project research through publications, organization of national symposia, and the program project website, the latter in collaboration with Core B, the Computational Resource and Dissemination Core. The core will in addition orchestrate new outreach mechanisms, such as workshops and tutorials, to com- municate the new methodology to practitioners. Through Administrative Offices at each institution, the core will coordinate all logistical functions, such as meeting scheduling, budget monitoring, coordination of reports, and arrangements for symposia. Overall, the core's structure and function will maximize the scientific integration of this multi-institutional effort.

Public Health Relevance

Core A: Administrative Core PROJECT NARRATIVE A program project of this scope and complexity requires careful and thoughtful administration. The Administra- tive Core (Core A), will provide essential administrative and scientific leadership, coordinating the investigators across three institutions into an effective team and facilitating integration of project research, effective dis- semination of research results, and management of resources and logistics. This oversight will ensure that the program project achieves its overarching goal to develop new statistical methods for personalized cancer medicine that will improve the health of cancer patients.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA142538-09
Application #
9451234
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
9
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Type
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Zhou, Jie; Zhang, Jiajia; Lu, Wenbin (2018) Computationally Efficient Estimation for the Generalized Odds Rate Mixture Cure Model with Interval-Censored Data. J Comput Graph Stat 27:48-58
Butler, Emily L; Laber, Eric B; Davis, Sonia M et al. (2018) Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules. Biometrics 74:18-26
Wong, Kin Yau; Zeng, Donglin; Lin, D Y (2018) Efficient Estimation for Semiparametric Structural Equation Models With Censored Data. J Am Stat Assoc 113:893-905
Wang, Charlotte; Tzeng, Jung-Ying; Wu, Pei-Zhen et al. (2018) Reexamining Dis/Similarity-Based Tests for Rare-Variant Association with Case-Control Samples. Genetics 209:105-113
Wu, Jing; Ibrahim, Joseph G; Chen, Ming-Hui et al. (2018) Bayesian Modeling and Inference for Nonignorably Missing Longitudinal Binary Response Data with Applications to HIV Prevention Trials. Stat Sin 28:1929-1963
Li, Zhiguo; Wang, Xiaofei; Wu, Yuan et al. (2018) Sample size calculation for studies with grouped survival data. Stat Med 37:3904-3917
Wang, Chun; Chen, Ming-Hui; Wu, Jing et al. (2018) Online updating method with new variables for big data streams. Can J Stat 46:123-146
Ni, Ai; Cai, Jianwen (2018) Tuning Parameter Selection in Cox Proportional Hazards Model with a Diverging Number of Parameters. Scand Stat Theory Appl 45:557-570
Teran Hidalgo, Sebastian J; Wu, Michael C; Engel, Stephanie M et al. (2018) Goodness-Of-Fit Test for Nonparametric Regression Models: Smoothing Spline ANOVA Models as Example. Comput Stat Data Anal 122:135-155
Jung, Sin-Ho (2018) Phase II cancer clinical trials for biomarker-guided treatments. J Biopharm Stat 28:256-263

Showing the most recent 10 out of 549 publications