Data lead to answers.

Fundamental to public health research and policy, biostatistics is also one of the most interdisciplinary departments at Boston University School of Public Health. By designing studies, developing new methodologies, and extracting and analyzing information from data, we help inform decisions to promote better health.

Biostatistics faculty members are internationally recognized for methodological innovations in clinical trials and observational studies, statistical genetics analysis, and Bayesian methods. They have a long history of collaborating to address some of the world’s most pressing public health concerns, as well as training the next generation of students to tackle emerging public health and medical issues with cutting-edge methods and technological skills.

Areas in which we are active include genetic studies of risk factors for breast cancer; safety and efficacy assessments of a new Alzheimer’s disease drug; comparisons of patient outcomes with different behavioral interventions; and studies to identify genetic and non-genetic factors of healthy aging and extreme human longevity.

Affiliated Academic Programs:

MS in Biostatistics MS in Applied Biostatistics

PhD in Biostatistics Master of Public Health

Recent Research in Biostatistics

Latest Publications

  • Published On 4/1/2023Diabetes Stigma and Clinical Outcomes in Adolescents and Young Adults: The SEARCH for Diabetes in Youth Study.Diabetes careread at PubMed
  • Published On 3/16/2023Longitudinal association between overweight years, polygenic risk and NAFLD, significant fibrosis and cirrhosis.Alimentary pharmacology & therapeuticsread at PubMed
  • Published On 3/16/2023Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-analysis of Community-Based Cohorts.Neurologyread at PubMed
  • Published On 3/15/2023Plasma Progerin in Patients With Hutchinson-Gilford Progeria Syndrome: Immunoassay Development and Clinical Evaluation.Circulationread at PubMed
  • Published On 3/15/2023Validation of an administrative algorithm for transgender and gender diverse persons against self-report data in electronic health records.Journal of the American Medical Informatics Association : JAMIAread at PubMed

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