- On-campus Program (Longwood Campus)
- 42.5 Credits Required to Graduate
- Thesis Required: mentor from home institution required for admission (please see below)**
- Program is run between July-August
- Can be completed in 3 Summers
- Previous STEM Experience Required (i.e. MDs, PhDs, or Master Level)
The Summer option/42.5 Credit is designed for applicants with a medical degree or master’s-level background in relevant disciplines (e.g., biology, chemistry, genetics, physiology, bioengineering, and related social and computational sciences) and can be completed over 3 summer semesters. A thesis proposal and a local mentor is required for application. A Thesis is required for this degree. The program begins with either the Summer Program in Clinical Effectiveness or the Session for Public Health Studies.
Questions regarding this program can be directed to either our Faculty Director, Pamela Rist (prist@mail.harvard.edu), or our program administrator Jeffrey Noyes (jnoyes@hsph.harvard.edu).
**Applicants to the Summer Only 42.5 credit Master of Science degree are required to submit a one-page thesis/research project proposal and identify a mentor at their home institution within their SOPHAS application. The thesis proposal should include a description of what the applicant might pursue for a thesis and identify the applicant’s mentor from their home institution including name, title, and contact information. The proposal will not be reviewed for scientific merit, only feasibility.**
For further information, please visit the Clinical Epidemiology webpage for important details on this program.
Competencies
By the end of the program, it is anticipated that the student will acquire the ability to:
1. Critically evaluate and apply principles of epidemiologic methods, including exposure and outcome measures, measures of association, bias and confounding, and study design options.
2. Demonstrate the ability to critically evaluate and apply appropriate biostatistical techniques for data arising from evaluation of public health problems (e.g., including basic probability theory and common distributions, effect measure estimation, continuous and categorical data analysis, parametric and non-parametric hypothesis tests, confidence intervals and p-values, correlation and basic regression techniques, and power/sample size calculations).
3.Apply appropriate biostatistical modeling methods using software packages (e.g., Stata, SAS, or R) to perform multivariable data analyses including control of confounding and detection of effect modification.
4. Evaluate and synthesize epidemiological studies published in the medical and public health literature.
