The PPP will build upon the success of existing pilot project programs and research training initiatives at UMN and UAB, specifically those that promote two-way research collaboration between community and academic investigators. Both institutions have a long track record of conducting research in partnership with the community on local, state, and regional levels. These projects have entailed establishing coalitions, building community capacity, and training more than 1,200 community volunteers. Further, both institutions have existing fiscal and administrative capacity to generate rapid awards to pilot project recipients and administer necessary contracts. In addition, the academic partners have a cadre of experienced grant reviewers with direct knowledge of community-based participatory research (CBPR) principles, health disparities, and men's health;and grant review materials?score sheets, review protocols, and acceptance/rejection letters;as well as lessons plans, presentations, manuals, and fact sheets that can be tailored to the needs of community-based pilot project investigators. For example, the UAB MHRC has awarded $625,000 in the form of projects to community coalitions in 6 states, hosted 5 regional technical assistance meetings, and provided technical assistance for the implementation of sub-recipients'activities through 68 sub-recipient conference calls and meetings. Finally, both institutions have successful research training, mentoring, and career-development programs for junior faculty interested in health disparities research. This wealth of experience and expertise will ensure the success of the proposed PPP.

National Institute of Health (NIH)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZMD1)
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University of Alabama Birmingham
United States
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Chen, Liddy M; Ibrahim, Joseph G; Chu, Haitao (2014) Sample size determination in shared frailty models for multivariate time-to-event data. J Biopharm Stat 24:908-23
Chen, Yong; Liu, Yulun; Ning, Jing et al. (2014) A composite likelihood method for bivariate meta-analysis in diagnostic systematic reviews. Stat Methods Med Res :
Ma, Xiaoye; Chen, Yong; Cole, Stephen R et al. (2014) A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias. Stat Methods Med Res :
Chen, Liddy M; Ibrahim, Joseph G; Chu, Haitao (2014) Flexible stopping boundaries when changing primary endpoints after unblinded interim analyses. J Biopharm Stat 24:817-33
Ho, Yen-Yi; Baechler, Emily C; Ortmann, Ward et al. (2014) Using gene expression to improve the power of genome-wide association analysis. Hum Hered 78:94-103