The proposed Program Project, Statistical Informatics for Cancer Research, will tackle a wide range of challenging statistical problems arising from large, complex datasets arising from population-based studies in cancer. The Administrative Core will be responsible for providing scientific and administrative leadership for the entire Program.
Specific aims are: 1. To facilitate intellectual exchange and collaboration between all Program members through the organization of bi-weekly meetings that will alternate between informal working group and more formal seminar meetings. Seminars will be open to the broader HSPH community in an effort to stimulate interest in quantitative issues for population based studies in cancer; 2. To plan and implement short-courses and visitor programs on topics relevant to the Program mission so as to ensure that all research supported by the Project is of highest quality and based on cutting edge methods; 3. To mentor junior members of the Program (postdoctoral fellows and junior faculty); 4. To communicate clearly with and provide accountability to individual Project Leaders and Co- Leaders, the Director of the Statistical Core and the Battelle Project Manager to ensure that appropriate progress is being made on all Program Aims 5. To manage all administrative aspects of the Program, including financial decision making and reporting and annual grant reports. 6. To ensure effective dissemination of the developed new methodology to real world practices through user-friendly open access software developments, applications of the proposed methods to the motivating cancer data, publications in both statistical and subject-matter conferences, and presentation of results at both statistical and subject-matter conferences. The Core will be co-directed by two accomplished biostatisticians, Professors Louise Ryan and Xihong Lin, both of whom are also highly experienced and competent administrators.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA134294-05
Application #
8379458
Study Section
Special Emphasis Panel (ZCA1-RPRB-7)
Project Start
Project End
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
5
Fiscal Year
2012
Total Cost
$78,345
Indirect Cost
$23,583
Name
Harvard University
Department
Type
DUNS #
149617367
City
Boston
State
MA
Country
United States
Zip Code
02115
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Wilson, Ander; Zigler, Corwin M; Patel, Chirag J et al. (2018) Model-averaged confounder adjustment for estimating multivariate exposure effects with linear regression. Biometrics 74:1034-1044
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