Data analytics identify the top-performing practices in our research communities. The CTSC facilitates the integration of research with health systems management as well as with the community. We aim to encourage and expand program-wide inclusion of statistical and epidemiological collaborations in translational research studies. The programs listed below can provide researchers with guidance on optimal study design and analysis plans that lead to transparent and reproducible research. This includes developing and using novel innovative designs and analyses as needed.
The CTSC BERD comprises experts in epidemiology and biostatistics across the CTSC's Partner Institutions. They provide a shared infrastructure of epidemiological and biostatistical resources to support CTSC researchers in three key areas:
- Development of optimal study designs and statistical analysis plans for study protocols: BERD experts provide free support for the development of research protocols submitted to funding agencies. Support typically includes development of an appropriate study design, statistical analysis plan, and corresponding budget for statistical support. When an investigator requests protocol development support, a BERD member will contact the investigator to discuss the availability of BERD support within 48 hours of the request. Requests made less than 4 weeks in advance of a deadline are not guaranteed to receive BERD support.
- Development of novel study designs and statistical methods that can be applied to translational research: BERD experts in statistical modeling, medical imaging, health outcomes research, informatics, statistical genetics, and genomics develop collaborative relationships with CTSC researchers interested in developing novel methodologies or statistical analysis tools. These collaborations often address problems that lack off-the-shelf solutions and accelerate movement along the 'discovery pathway' from laboratory to improved human health.
- Educating and mentoring early stage investigators (basic scientists, clinicians, epidemiologists, and biostatisticians) in study design and statistical analysis: Through a variety of seminars, workshops, and courses, BERD experts educate early stage investigators in topics ranging from study design to statistical analysis. BERD experts also mentor early stage investigators both informally (via office hours) and formally (by serving as advisors on thesis committees or named mentors on career development awards).
To learn more about CTSC BERD experts at each of the three CTSC Partner Institutions, please visit the following websites:
The CTSC offers biostatistical services depending on your research needs. In the Case Comprehensive Cancer Center, the Biostatistics & Bioinformatics Core Facility (BBCF) provides and coordinates statistical, bioinformatics, and clinical informatics research support in the design, planning, conduct, analysis, and reporting of research studies. If you are interested in biostatistical support for your microarray data, the DNA and Next Generation Sequencing Core Facility provides assistance in all facets of experimentation from design to data analysis, including grant and manuscript preparations.
The core is focused on developing capacity to conduct population-based and outcomes research using population-based databases.
Services available for research involving population-based databases include:
- Advice and assistance to researchers on appropriate study design and data source(s)
- Access to appropriate database(s) and the ability to obtain the necessary data users' agreements and IRB approvals
- Analytic support to carry out the study
- Databases available through the Core's archive:
- Ohio Medicaid enrollment and claim forms (1991-2008)
- The Cancer Aging Linked Database (1997-2001)
- The Health and Retirement Study
- Hospital Discharge data
- National Inpatient Sample (NIS) databases (1988-2007)
- State Inpatient Databases (SID) for various states/years
- Linked data from the Ohio Department of Mental Health (ODMH) and death certificate data (2004-2007)
Continue to the Department of Population & Quantitative Health Sciences website