The Master’s in Biostatistics program requires 31 credits. It can be completed in one year or students may choose to do the program at a slower or part-time pace.
Following the one-year program, students study across the fall/spring/summer semesters. The final, summer semester consists of an internship or practicum that can be done locally in Cleveland or elsewhere, as the required summer course is offered online.
General Requirements (31 credits):
- Core curriculum semester courses (15 semester credits), plus:
- Track-required courses (12 semester credits)
- Biostatistical Consulting (1 semester credit) PQHS 502
- Internship/Practicum (3 semester credits) PQHS 602
- A written report from the internship/practicum serves as the final MS exam
Core Curriculum Courses (15 credits):
- Data Management and Statistical Programming (3 credits) PQHS 414
- Statistical Methods in Biological and Medical Sciences I (3 credits) PQHS 431
- Statistical Methods in Biological and Medical Sciences II (3 credits) PQHS 432
- Categorical Data Analysis (3 credits) PQHS 453
- Introduction to Epidemiology (3 credits) PQHS 490
Track required courses (12 semester credits) are selected from one of the following tracks:
- Biostatistics – Generalist Track
- Genomics and Bioinformatics
- Health Care Analytics
- Social and Behavioral Science
Biostatistics – Generalist Track
Track Leader: Abdus Sattar, PhD
Students following the generalist biostatistics track will receive balanced training in biostatistical theories and methods. Students will gain mastery of basic probability theory and statistical inference, learn the methods of survival and longitudinal data analysis, and still have the flexibility to choose an elective from advanced courses.
The instruction in methods and theory, as well as the hands-on analytical training supports the pursuit of an advanced relevant degree and/or work as a master’s prepared biostatistician in various settings, including academia, industry (especially in pharmaceutical research), and government agencies.
Track-Required Courses:
- Basics of Probability and Statistical Theory (PQHS 430)
- Introduction to Mathematical Statistics (PQHS 480)
- Survival Data Analysis (PQHS 435)
- Longitudinal Data Analysis (PQHS 459)
- One of the following courses:
- Multivariate Analysis and Data Mining (STAT 426)
- Clinical Trials (PQHS 450)
- Machine Learning and Data Mining (PQHS 471)
Genomics and Bioinformatics
Track Leader: Frederick Schumacher, PhD, MPH
Students will be trained to work in genomics and bioinformatics. In addition to the basics in biostatistics, they will learn the designs, methods, techniques, and tools that are commonly used in genetic epidemiology, statistical genomics, and bioinformatics research. Big Data methods of data mining and machine learning are also required in this track. This training prepares graduates for positions as analysts, statisticians and bioinformatics specialists on a genomics or genetic epidemiology research team in a research institute/university, pharmaceutical or biotech company.
Track-Required Courses:
- Introduction to Genomics and Human Health (PQHS 451)
- Statistical Methods in Genetic Epidemiology (PQHS 452)
- Design & Analysis of Sequencing Studies (PQHS 457)
- Machine Learning & Data Mining (PQHS 471)
Health Care Analytics
Track Leader: Thomas Love, PhD
Biostatistics is a vital part of clinical research, which includes both observational studies and randomized clinical trials. Modern clinical, or patient, research applies innovative methodologies for the design and analysis of such studies to increase the likelihood of success and minimize patient burden and the use of scarce resources.
Clinical research biostatisticians work as part of multi-disciplinary teams with clinical and statistical investigators to develop and execute study designs and analyze plans with scientific rigor. They also support teams in meeting regulatory requirements by sanctioning bodies and funding agencies. Principal roles include the design, analysis, coordination and reporting of observational and trial-based clinical research studies.
Most of a health care analysts’ or clinical research biostatisticians’ work is dedicated to evaluating, executing and reporting on well-designed studies so as to help investigators meet their scientific objectives. Training through this track prepares graduates for roles as biostatistician; lead, senior or principal biostatistician; consulting statistician; statistical researcher; statistical programmer; clinical informatics strategist; data scientist; and clinical research manager. Such positions require strong written and verbal communication skills, and the ability to work as part of a team with subject matter experts on protocol development and statistical reporting.
Biostatisticians completing the Health Care Analytics track will be well-positioned to apply for positions in industry, academia (including teaching hospitals) and government. Recent graduates of similar programs have found excellent positions with pharmaceutical companies, university and health system-based research groups, and within various health industries.
Track-Required Courses:
- Survival Analysis (PQHS 435)
- Large Health Care Databases and Electronic Health Records (PQHS 515)
- Two of the following courses:
- Longitudinal Data Analysis (PQHS 459)
- Observational Studies (PQHS 500)
- Clinical Trials (PQHS 450)
- Machine Learning and Data Mining (PQHS 471)
Social and Behavioral Science
Track Leader: Arin Connel, PhD
Students in this track are trained to collaborate as analysts and research assistants in the social and behavioral sciences, including anthropology, sociology, psychology and social work. Students are prepared to partner in study designs and analysis on a wide range of research projects focused in social and behavioral health and science.
This track was designed for students whose undergraduate work involved a major or minor in one of the social and behavioral sciences, and who want to pursue work as research analysts and team biostatisticians, who bring to the team their training in the field along with qualitative and quantitative analysis. Our graduates are prepared for positions as research managers and team biostatisticians in academic/research institutes or government agencies.
Track-Required Courses:
- Longitudinal Data Analysis (PQHS 459)
- Measurement of Behavior (PSCL 412 or PQHS 412)
- Structural Equation Modeling (NURS 632)
- Qualitative and Mixed Methods (MPHP 482)