The Administrative Core (Core A) is responsible for organizing the program investigators and staff into an effective and well-coordinated team to develop and implement the statistical methods for cancer clinical trials proposed in the research projects to improve the health of cancer patients. This program is integrated across three institutions whith a lead PD/Pl at one institution (UNC-CH) and two additional PD/PIs at the other two institutions (NCSU and Duke). These three PD/PIs form an executive Committee with overall responsibility for the management and administration of the program. Each institution has an additional co-PD/PI to assist the PD/PIs with both the overall and intra-institutional administration of the program project. The Executive Committee, three co-PD/PIs. and individual project leaders form a Steering Committee which provides overall scientific guidance for the program. An External Advisory Committee of experts provides feedback to the Steering Committee on the goals and progress of the program during an annual retreat. Communication and collaboration between project investigators is facilitated with a program project wiki. Communication and dissemination of new results and software are aided with a program project web page. The matrix leadership structure of Core A maximizes the scientific integration of this multi-disciplinary and trans-institutional collaboration.

Public Health Relevance

The Administrative Core (Core A) is essential to the success of the proposed project since it coordinates all administration and provides leadership for the five projects, three cores and three institutions involved in this program project. The administrative component is necessary to facilitate the science of this program project and to achieve the overall program aims, to develop new statistical methods 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 #
5P01CA142538-02
Application #
8245194
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2011-04-01
Budget End
2012-03-31
Support Year
2
Fiscal Year
2011
Total Cost
$209,747
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Type
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
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
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
Li, Tengfei; Xie, Fengchang; Feng, Xiangnan et al. (2018) Functional Linear Regression Models for Nonignorable Missing Scalar Responses. Stat Sin 28:1867-1886
Pietryk, Edward W; Clement, Kiristin; Elnagheeb, Marwa et al. (2018) Intergenerational response to the endocrine disruptor vinclozolin is influenced by maternal genotype and crossing scheme. Reprod Toxicol 78:9-19
Jung, Sin-Ho (2018) Phase II cancer clinical trials for biomarker-guided treatments. J Biopharm Stat 28:256-263
Psioda, Matthew A; Ibrahim, Joseph G (2018) Bayesian design of a survival trial with a cured fraction using historical data. Stat Med 37:3814-3831
Zhou, Qingning; Cai, Jianwen; Zhou, Haibo (2018) Outcome-dependent sampling with interval-censored failure time data. Biometrics 74:58-67
Psioda, Matthew A; Ibrahim, Joseph G (2018) Bayesian clinical trial design using historical data that inform the treatment effect. Biostatistics :
Shi, Chengchun; Song, Rui; Lu, Wenbin et al. (2018) Maximin Projection Learning for Optimal Treatment Decision with Heterogeneous Individualized Treatment Effects. J R Stat Soc Series B Stat Methodol 80:681-702

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