Shared Resource Core

$294,732U54FY2025CANIH

Dana-Farber Cancer Inst, Boston MA

Investigators

Linked publications & trials

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Abstract

To address the critical gap in research among population groups that are at high risk for cancer in our research studies due to a lack of access, particularly by early-stage investigators, to high level methods expertise, the Research Design and Analysis Core (RDAC) will provide methodologists and statisticians to meet the needs of Partnership investigators and trainees. By bridging this gap in qualitative and mixed methods, the RDAC will maximize its impact on new lines of cancer research. Reaching across institutional and disciplinary divides, the RDAC will provide population and basic science studies with the methodologic expertise for proper study design and data acquisition/analysis, and infrastructure for data collection at individual-, organizational-, and community-levels with a focus to minimize data missingness, foster cross-institutional relationships, and provide students with novel educational opportunities. In addition, the RDAC will offer a broad spectrum of educational experiences to enhance the field of cancer research. We will provide mentorship and training in the design, implementation, and analysis of population science research to meet the needs of the Partnership research community and to facilitate sound clinical and basic science research. The RDAC aims to: 1) Address the gap/shortage of methodologists, the RDAC will provide methodological consultation, operational support, and mentorship for quantitative and qualitative cancer research projects; 2) Address problems with data missingness by providing investigators with cutting-edge, innovative experimental design and statistical methods; 3) Build methodological and statistical capability and expertise among all Partnership faculty, trainees and staff, as well as the broader community; and 4) Provide support to the other Partnership Cores for administrative activities, through program evaluation, educational programming, and data management/analysis.

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