PhD in Biostatistics

Overview

The PhD program aims to train independent researchers in biostatistics applications and methodology. The program includes the Master's program courses, comprehensive analysis of a dataset and reporting of results equivalent to the MS thesis, and at least one additional semester of advanced courses in statistical theory and methods. Students in the PhD program are also required to take courses toward a minor in biomedical science, pass both written and oral examinations, and successfully complete a doctoral dissertation.

Academic Advisor

Each incoming PhD student is assigned an academic advisor who serves as the student's primary mentor during the first two years of the program, advising in course selection and related academic matters. Once a thesis advisor is selected, s/he will normally assume the role of academic advisor for the remainder of the student's program. The Graduate Program attempts to assign advisors to students with similar backgrounds and interests. A student may petition to change academic advisors at any time by request to the Director of Graduate Studies.

Course Requirements

The PhD degree at the University of Pennsylvania requires a minimum of 20 course units. The PhD in Biostatistics typically requires five to six semesters of coursework plus additional semesters devoted to dissertation research. Full-time students making satisfactory progress can complete the degree in four or five years. The standard required course sequence for PhD students consists of 17 units in core courses, electives and courses in the minor: 8 units in statistical methods; 3 units in theory; 0.5 unit of anatomy/physiology and 0.5 unit of epidemiology, 2 units toward a minor, and 3 units of electives in advanced theory and methods. The remaining 3 required course units will typically consist of reading courses or additional advanced electives. The required courses are listed below.

* = core course covered in general examination.

Methods:

BSTA 630 Methods I (1.0 course unit)*
BSTA 631 Methods II (1.0 course unit)*
BSTA 651 Introduction to Linear Models and Generalized Linear Models (1.0 course unit)*
BSTA 652 Categorical Data Analysis (1.0 course unit)*
BSTA 653 Survival Analysis (1.0 course unit) *
BSTA 656 Longitudinal Data Analysis (1.0 course unit)
BSTA 659 Design of Biomedical Studies (1.0 course unit)
BSTA 670 Statistical Computing (1.0 course unit)

Theory:

BSTA 620/STAT 510 Probability I (1.0 course unit)*
BSTA 621/STAT 512 Statistical Inference I (1.0 course unit)*
BSTA 622/STAT 550 Statistical Inference II (1.0 course unit)

Applications:

BSTA 510 Introduction to Human Health and Diseases (0.5 course unit)
BSTA 509 Introductory Epidemiology (0.5 course unit)*

Elective Courses

A minimum of 6 course units of advanced elective courses is required for the PhD. A partial listing of possible electives is shown below. Note that not all of these courses are offered every year. Offerings for the new academic year are made available each fall.

BSTA 751 Advanced Methods for Linear and Nonlinear Models (1.0 course unit)
BSTA 752 Categorical Data Analysis II (1.0 course unit)
BSTA 753 Survival Analysis II (1.0 course unit)
BSTA 754 Experimental Design II (1.0 course unit)
BSTA 755/STAT 925 Multivariate Analysis: Methods (1.0 course unit)
BSTA 756/STAT 926 Multivariate Analysis: Theory (1.0 course unit)
BSTA 770/STAT 915 Nonparametric Inference (1.0 course unit)
BSTA 771 Applied Bayesian Analysis (1.0 course unit)
BSTA 772 Statistical Methods for the Design and Analysis of Clinical Trials (1.0 course unit)
BSTA 774 Statistical Methods for Evaluating Diagnostic Tests (0.5/1.0 course unit)
BSTA 775/STAT 920 Sample Survey Methods (1.0 course unit)
BSTA 781 Asymptotic Theory with Biomedical and Psychosocial Applications (1.0 course unit)
BSTA 782 Statistical Methods for Incomplete Data (1.0 course unit)
BSTA 783 Multivariate and Functional Data Analysis (1.0 course unit)
BSTA 784 Analysis of Biokinetic Data (0.5 course unit)
BSTA 785 Statistical Methods for Genomic Data Analysis (1.0 course unit)
BSTA 786 Advanced Topics in Clinical Trials (1.0 course unit)
BSTA 787 Methods for Statistical Genetics in Complex Human Disease (1.0 course unit)
BSTA 790 Causal Inference in Biomedical Research (1.0 course unit)
BSTA 810/STAT 530 Probability II (1.0 course unit)
BSTA 811/STAT 531 Stochastic Processes (1.0 course unit)
BSTA 812/STAT 955 Seminar in Probability Theory (1.0 course unit)
BSTA 820/STAT 552 Statistical Inference III (1.0 course unit)
BSTA 852/STAT 910 Forecasting and Time Series (1.0 course unit)
BSTA 854/STAT 927 Statistical Decision Theory (1.0 course unit)
BSTA 870/STAT 991 Seminar in Advanced Applications (1.0 course unit)
BSTA 871 TBD Computer Intensive Methods in Statistics
BSTA 890-899 TBD Special Topics Seminars

Biostatistics Consulting Workshop (Equivalent of MS Thesis and Teaching Practicum)

All PhD students must participate in the Biostatistics Consulting Workshop, typically during their first or second year. Each student will complete a comprehensive analysis of a dataset and report the results. The consulting workshop provides the basis of these projects for most students.

All students in the PhD program must spend at least one semester serving as a teaching assistant for one of the Department's core courses.

All PhD students are expected to attend the Biostatistics seminars.

Minor

Students must complete two units (typically two courses) in a minor field representing one or more areas of biomedical science. Some suggested areas for the minor courses include physiology, genetics, and psychology. Courses for the minor must be taken outside of the GGEB, except that the student may take as part of the minor courses in epidemiology beyond the required introductory course (BSTA 509). The student's dissertation advisor determines what courses constitute related topics, subject to this constraint.

Qualifications Evaluation Examination

A written qualifications evaluation examination covering material in the required courses for the PhD degree is offered each year after the fall semester. Most students take this exam after completing three semesters of coursework, but well prepared students may take it in their first year. Students must pass this exam to continue in the graduate program.

Candidacy Examination

To become a formal candidate for the PhD, a student must pass an candidacy examination, which generally focuses on the proposed dissertation research (see below) but may also cover related topics in biostatistics and the minor field. For additional information, see the University of Pennsylvania Graduate Catalog.

PhD Thesis

The PhD thesis is an original contribution to statistical methodology for biomedical applications. This can be accomplished either through a novel application of statistical methods to a given subject matter, the development of new statistical methods or theory, or a combination of new theory, methods and applications. Dissertation research culminates in a final dissertation examination, or thesis defense, which consists of an oral presentation by the candidate and an examination by the faculty. For details, see the Graduate Catalog.

Part-Time Students

Although full-time study is the ideal, the program also welcomes part-time PhD students. Because the training program requires that several courses be taken in sequence, and all courses are not offered each semester, completion of course requirements by part-time students may take several years. Part-time students should therefore work carefully with their academic advisors to develop an efficient program of study.

Transfer of Credit

At least twelve course units (typically three semesters) of the total required for the PhD degree must be completed while enrolled in a graduate program at the University of Pennsylvania. Transfer of credit is approved by the Director of the Biostatistics Graduate Program.

Academic Program Proposals and Approvals

At the beginning of each academic year, each student, in collaboration with his/her advisor, will prepare a proposal for the academic program including courses to be taken, courses to be transferred, and timelines for examinations and thesis preparation.

Typical Course Sequence for Full-Time Students in the Biostatistics PhD Program

Semester Required (credit) Required (non-credit)
1st Year: Fall BSTA 620 Probability I (1.0)
BSTA 630 Statistical Methods and Data Analysis I (1.0)
BSTA 509 Introductory Epidemiology (0.5)
BSTA 510 Introduction to Human Health and Diseases (0.5)
HIPAA Certification
POR Certification
1st Year: Spring BSTA 621 Statistical Inference I (1.0)
BSTA 631 Statistical Methods and Data Analysis II (1.0)
BSTA 651 Introduction to Linear Models & GLM (1.0)
Online RCR Symposium
Consulting Workshop
2nd Year: Fall BSTA 622 Statistical Inference II (1.0)
BSTA 652 Categorical Data Analysis (1.0)
BSTA 653 Survival Analysis (1.0)
Consulting II Project/ MS Thesis
Written Qualifying Examination Parts A & B (first week in January)
2nd Year: Spring BSTA 656 Longitudinal Data Analysis (1.0)
BSTA 659 Design of Biomedical Studies (1.0)
RCR Workshop
Completion of Consulting II Project/MS Thesis by deadline
3rd Year: Fall BSTA 670 Statistical Computing1 (1.0)
Advanced Elective
Minor
Teaching Assistantship2
3rd Year: Spring Minor
Advanced Elective
BSTA 999 Reading Course
RCR Workshop
Summer Dissertation proposal, Candidacy Examination
4th Year: Fall BSTA 999 Reading Course (2 course units)
BSTA 920 Dissertation Research (1 course unit)
Teaching Assistantship2
4th Year: Spring BSTA 920 Dissertation Research (3 course units) RCR Workshop
5th Year: Fall BSTA 920 Dissertation Research (3 course units) Teaching Assistantship2
5th Year: Spring BSTA 920 Dissertation Research (3 course units) RCR Workshop
1 Elective for MS students; material not covered on written qualifying exam.
2 One semester of teaching required in years 3-5.
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