Biostatistics
Doctor of Philosophy
Doctoral students with a concentration in Biostatistics are prepared for
conducting the following types of research in health or medicine:
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The design of comprehensive investigations;
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The novel employment of existing statistical methods to address meaningful
scientific questions;
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The development of new statistical methodologies with immediate application
to studies of the cause or treatment of disease.
Applicants should have a knowledge of the principles of biology and a strong
undergraduate record in mathematics, including course work in advanced calculus
and linear algebra.
Degree Requirements
- Required Classes:
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Seminar in Biostatistics
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Applied Regression Analysis
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Categorical Data Analysis
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Longitudinal Data Analysis
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Theory of Generalized Linear Models
Spatial Statistics in Public Health Summer Rotation in Statistical Research Applied Survival Analysis
(half-semester course) -
Design and Analysis of Epidemiologic Studies (half-semester course)
- Students will also take one of the following:
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Stochastic Processes in Biology and Medicine
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Theory of Survival Analysis and Its Applications
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Nonparametric Statistical Methods and Their Applications
- Theoretical Statistics
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Probability Theory
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Theory of Statistics
- Statistical Inference
- Linear Models
Under the guidance of the academic adviser,
students choose three courses in their applied area. The applied
area consists of an intended area of methodologic research applied
to such areas as epidemiology, genetics, microbiology, or health
policy.
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Comprehensive Examinations
The examination covering
epidemiological methods includes both an in-class and a take home portion.
One faculty member is responsible for coordinating this examination, and
the examination content is developed by the overall faculty. The specialty
area examination is usually developed by an expert in the field following discussions with the candidate and biostatistics advisor.
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Research Experience
In a number of courses, students gain actual experience with various
aspects of research including preparation of a research grant, questionnaire
design, preparation of a database for analysis, and analysis and interpretation
of real data. In addition, doctoral students can gain research experience
by working with faculty members on ongoing research studies prior to initiating
dissertation research.
- The Dissertation
The Division strives for doctoral dissertations
that have a strong methodological component motivated by an important health
question. Hence, the dissertation should include a methodological advance
or a substantial modfication of an existing method motivated by a set of
data collected to address an important health question. The dissertation
must also include the application of the proposed methodology to real data.
A fairly routine application of widely available statistical methodology
is not acceptable as a dissertation topic. Candidates are expected not
only to show a thorough knowledge of the posed health question, but also
to demonstrate quantitative skills necessary for the creation and application
of novel statistical tools.
Research projects carried out by recent Biostatistics graduates
- Bayesian Design and Monitoring of Clinical Trials
- A
Bayesian Approach to Modeling Space Time Infectious Disease through
the Allocation of Unconfirmed Cases
- Integration of Biological Information into Yeast Modeling System
- A Latent Variable Model for Linkage Analysis
- Statistical
methods for paired survival time data. Application to longevity
in twins, renal failure times, and otitis media
- Statistical
Methods for Haplotype Analysis in Genetic Studies
- Statistical Design and Analysis for Post-Marketing Studies of Rare
Adverse Events
- Proteomics
Funding Opportunities
Many faculty have grants which can be supplemented to provide training related
expenses and stipends to students. In addition, there are some opportunities
for University fellowships and for NIH traineeships for those interested
in studying statistical methods with applications in
Learning Objectives
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Ph.D. at the Graduate School |
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