The proposed Program Project, Statistical Informatics for Cancer Research, will tackle a wide range of challenging statistical problems arising from large, complex datasets in population-based studies in cancer. The Administrative Core will be responsible for providing scientific and administrative leadership for the entire Program.
The specific aims are: (1) To facilitate intellectual exchange and collaboration between all Program members through organizing monthly P01 group meetings, a series of bi-weekly seminars and an annual retreat. Seminars will be open to the broader HSPH community in an effort to stimulate interest in quantitative issues for population based studies in cancer and disseminate findings of the Program Project; (2) To set priorities, and oversee the progress and evaluation of the Program to ensure that appropriate progress is being made and effective communications between the Program investigators, and to work with the External Advisory Committee to monitor and evaluate the progress of the Program Project. (3) To plan short-courses, workshops and visitor programs on topics relevant to the Program mission so as to ensure that all research supported by the Program Project is of high quality and based on cutting edge methods and integrated with substantive cancer areas;(4) To mentor junior members of the Program (postdoctoral fellows and junior faculty);(5) To manage all administrative aspects of the Program, including financial decision making and reporting and annual grant reports;(6) To work with the Statistical Computing Core to ensure appropriate computing support is provided, and 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 Xihong Lin and Francesca Dominici, both of whom are also highly experienced and competent administrators.

Public Health Relevance

The Program Project aims to use rich data sources to develop effective strategies for reducing cancer burden in the U.S. and improving longevity and quality of life. The Administrative Gore takes a scientific and administrative leadership of the Program by facilitating exchange and communication among Program participants to maximize the likelihood of accomplishing the mission of the Program.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Program Projects (P01)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1-RPRB-2)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Harvard University
United States
Zip Code
Bind, M-A C; Vanderweele, T J; Coull, B A et al. (2016) Causal mediation analysis for longitudinal data with exogenous exposure. Biostatistics 17:122-34
Hernán, Miguel A; Robins, James M (2016) Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available. Am J Epidemiol :
Chen, Jun; Just, Allan C; Schwartz, Joel et al. (2016) CpGFilter: model-based CpG probe filtering with replicates for epigenome-wide association studies. Bioinformatics 32:469-71
Lin, Xinyi; Lee, Seunggeun; Wu, Michael C et al. (2016) Test for rare variants by environment interactions in sequencing association studies. Biometrics 72:156-64
Lee, Kyu Ha; Tadesse, Mahlet G; Baccarelli, Andrea A et al. (2016) Multivariate Bayesian variable selection exploiting dependence structure among outcomes: Application to air pollution effects on DNA methylation. Biometrics :
Yung, Godwin; Lin, Xihong (2016) Validity of using ad hoc methods to analyze secondary traits in case-control association studies. Genet Epidemiol 40:732-743
Arvold, Nils D; Cefalu, Matthew; Wang, Yun et al. (2016) Comparative effectiveness of radiotherapy with vs. without temozolomide in older patients with glioblastoma. J Neurooncol :
Wasfy, Jason H; Dominici, Francesca; Yeh, Robert W (2016) Letter by Wasfy et al Regarding Article, "Facility Level Variation in Hospitalization, Mortality, and Costs in the 30 Days After Percutaneous Coronary Intervention: Insights on Short-Term Healthcare Value From the Veterans Affairs Clinical Assessment, Rep Circulation 133:e376
Carere, Deanna Alexis; Kraft, Peter; Kaphingst, Kimberly A et al. (2016) Consumers report lower confidence in their genetics knowledge following direct-to-consumer personal genomic testing. Genet Med 18:65-72
Zigler, Corwin Matthew (2016) The Central Role of Bayes' Theorem for Joint Estimation of Causal Effects and Propensity Scores. Am Stat 70:47-54

Showing the most recent 10 out of 136 publications