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University of Colorado Denver

 

Doctor of Philosophy

Biostatistics


The PhD in Biostatistics prepares students for advanced study and research in biostatistics.  The program targets students with strong skills and training in mathematics and statistics who are interested in applications in health care and biological settings.

PhD Biostatisticians typically function as independent investigators or key collaborators and co-investigators with researchers in other areas.  In this function they take the lead in designing studies and analyses.  Many continue to teach and carry out research developing new statistical methods.  Areas of faculty research include analysis of longitudinal data, clinical trials, statistical methods in genetics and genomics, causal modeling, treatment of missing data and imputation, and power and sample size analysis.

Coursework (beyond the MS in Biostatistics) includes: advanced applied statistics; advanced theoretical statistics; and electives in a health care or biological area of the student’s choice.

For students with an MS in biostatistics or a related field the program can be completed in three to four years, with most of the first one to two years devoted to coursework and most of the later years to research and dissertation. Research and dissertation work involves developing, comparing and evaluating statistical methods (e.g. methods for analyzing data), typically motivated by an application in health care or biology.

 

Program Requirements - PhD Biostatistics

 

COURSE REQUIREMENT

COURSE #

CREDITS

Required MS Biostatistics Courses

 

    20

Elective MS Biostatistics Courses 

 

     5 

Required Public Health Courses

 

     6

Foundations in Public Health

Public Health Elective

PUBH 6600

     2

     1

Epidemiology

EPID 6630

     3

Required PhD Biostatistics Courses

     6

Advanced Mathematical Statistics I

BIOS 7731

     3

Advanced Mathematical Statistics II

BIOS 7732

     3

Elective PhD Biostatistics Courses

(Courses not listed require director approval)

 

     9

 

Statistical Methods in Genomics

BIOS 7659

     3

Analysis of Correlated Data

BIOS 7712

     1

Statistical Methods for Missing Data

BIOS 7713

     2

​Advanced Statistical Computing

​BIOS 7714

     ​3

​Stochastic Modeling

​BIOS 7715

     ​2

​Topics in Statistical Genetics

​BIOS 7716

     ​1

Elective Health Sciences Courses

 

     3

Dissertation

BIOS 8990

    30

TOTAL PROGRAM CREDITS

 

    79

 

PhD Biostatistics Competencies

Identifier
PhD Biostatistics Competencies
Collaboration: Work collaboratively with biomedical or public health researchers on the design, implementation, data analysis and dissemination of research studies.
PHD-BIOS 1​​
Write or modify study aims so that the aims map to testable hypotheses.
PHD-BIOS 2
Develop and refine the design of studies including appropriate formulation of the study aims, parameterization of the underlying research questions, and evaluation of study information requirements (sample size). Modify and develop new study designs when existing/initial approaches are inadequate.
PHD-BIOS 3
Identify, implement, and correctly interpret appropriate data analysis approaches for study aims, and suggest new methods when existing approaches are inadequate.
PHD-BIOS 4
Obtain basic understanding of biomedical or public health subject matter for collaborative project.
PHD-BIOS 5
Establish and foster effective communication with non-statistician collaborators in written, graphical and verbal forms during the lifetime of the project.
Biostatistical Research: Develop and disseminate new biostatistical design, estimation or hypothesis testing approaches.
PHD-BIOS 6
Read (bio) statistical literature on a subject area and synthesize the strengths and weaknesses of existing research.
PHD-BIOS 7
Use statistical theory and biological/public health knowledge to propose new statistical methods to solve statistical problems deriving out of biomedical/public health research.
PHD-BIOS 8
Use appropriate theory or design and implement appropriate simulation studies to exhibit that new methodology has sound statistical features.

 

 

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