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New Analytics Center for Cardiovascular Medicine
Cardiovascular Medicine Analytics Center (CMAC)
The Cardiovascular Medicine Analytics Center (CMAC) provides biostatistics, study design, and data analytics support tailored to cardiovascular research at Yale. Our team pairs advanced statistical methods with a deep understanding of cardiovascular medicine to help investigators design strong studies, win funding, and publish rigorous results.
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Fill out this intake form to schedule a consultation on grant proposals, research projects, and investigator-initiated studies with funding support.
Mission
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To serve and partner with the Cardiovascular Medicine community by providing the biostatistical and data management expertise needed to run efficient, statistically rigorous clinical studies, and conduct sound clinical and translational research.
Goals
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- To provide statistical expertise on the design, conduct, analysis, and interpretation of clinical and translational research studies
- To ensure the quality and integrity of data and analyses
- To support grants in Cardiovascular Medicine
- To support industry-funded and investigator-initiated studies
- To support ongoing and new important research
- To educate members of the department and fellow trainees in statistical methodology and the nuances of statistical approaches
- To maintain expertise in state-of-the-art analysis techniques commonly employed in the cardiovascular space
- To innovate by developing new statistical methodology as needed to solve complex questions that may result from collaborations within the group
Our Expertise
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CMAC supports cardiovascular investigators at every stage of a study, from the first idea through publication.
| Stage | How we help |
|---|---|
| Plan and get funded | Study design, sample size and power calculations, statistical sections and analysis plans for grant applications, budgets for biostatistics effort |
| Run the study | Randomization, data management and quality checks, interim analyses and DSMB reports for clinical trials |
| Analyze | Rigorous analysis of trial, registry, EHR and observational data; causal inference; Bayesian and computationally intensive methods |
| Publish and share | Interpretation of results, tables and figures, statistical methods sections, responses to reviewers, reproducible code |
| Learn | Training for faculty, fellows, and trainees in statistical methods and their practical nuances |
| Innovate | New statistical methods when standard approaches are not enough for a complex research question |
Fill out this intake form to schedule a consultation on grant proposals, research projects, and investigator-initiated studies with funding support.