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Doctor of Philosophy in Biostatistics-Decision Science

Major: BDSCPHDBIO
Degree Awarded: Ph.D.
Unit: GH
Program Webpage: http://louisville.edu/sphis/bb/academics


Program Information

Biostatistics involves the development and application of statistical techniques to scientific research in health-related fields, including medicine, epidemiology, and public health. Students in the Ph.D. program receive state-of-the-art training in the latest statistical methodology in order to tackle the challenges associated with the study design and data analysis of modern research conducted in the health sciences. The Ph.D. program provides advanced training in biostatistical theory and methods, with the goal of enabling the student to carry out original research. In addition, students may elect to train with an emphasis on decision science or on bioinformatics.

Biostatistics involves the development and application of statistical methods in research in health-related fields, including public health, medicine, dentistry, and nursing. This program is designed to train students in biostatistics for carrying our research in biomedical fields and in statistical methods used in biomedical research.

Decision science, or formal decision analysis, is an emerging, cutting edge discipline that provides researchers with additional tools with which to develop the clinical and health-care policies and guidelines that affect public health. The decision science emphasis goes beyond traditional decision science programs by providing a mathematically rigorous, interdisciplinary approach to decision-making that is capable of adapting to the ever-changing health care environment. The decision science emphasis provides advanced training in the theory and methods of formal decision analysis, with the goal of enabling students to carry out original research. The focus of is on training a well-qualified biostatistician to work within the specialized field of decision science.

Bioinformatics requires the development and application of statistical methods for many of the areas covered by the field, including genomics, proteomics, statistical genetics, and metabolomics. Current biomedical research technologies generate high volumes of data that require extension of existing statistical methodologies and development of new methodologies in order to extract important information regarding biological processes. The emphasis on bioinformatics is designed to fulfill the expanding need for biostatisticians with advanced training in this area. Students in the bioinformatics emphasis gain a basic understanding of molecular and cellular biology, genetics, and bioinformatics and an in-depth knowledge of statistical theory and methods. Graduates are able to carry out original statistical research in genomics, proteomics, metabolomics, and evolving areas of systems biology.

Students who complete the M.S. program in biostatistics with the Department of Bioinformatics and Biostatistics or who already possess the equivalent of an M.S. in statistics, biostatistics, decision science, or a related discipline may apply for admission to the Ph.D. program.The Ph.D. program in biostatistics is located in the Department of Bioinformatics and Biostatistics.

Competencies
To graduate, a student must be able to demonstrate mastery of the following competencies:

 

Competency

Demonstration*

QE

SCP

Dsrt

 

Read, interpret, and critically review the biostatistics content of scientific and biomedical journal articles

x

 

x

Analyze moderately complex research data using statistical methods involving common linear statistical models

x

x

 

Analyze dichotomous, count, and time-to-event data using appropriate statistical methods, including logistic regression, log-linear models, Kaplan-Meier curves, and Cox proportional hazards models

x

x

 

Assist researchers in planning research studies, proposing and evaluating statistical methods and computing power analyses

 

x

 

Write statistical methods sections for grant proposals, clinical trial protocols, and journal articles

x

 

 

Manage data using spreadsheet and database software

x

 

 

Use standard statistical and graphics computer packages including SAS, R, and SPSS

x

x

x

Keep abreast of statistical methods literature to evaluate and utilize new statistical methods

 

 

x

Thoroughly understand the broad discipline of biostatistics, including its theoretic underpinnings, its history of development, current applications, and areas of active inquiry

x

 

x

Understand advanced biostatistical operations

x

 

x

Conduct independent research

 

 

x

Advance the field of biostatistics through original research

 

 

x

 

Students who elected to have an emphasis must demonstrate the following additional competencies, many of which represent specialization of competencies cited above:

 

Additional Competency by Emphasis

Demonstration*

QE

SCP

Dsrt

 

Emphasis on Decision Science

Read and critically evaluate decision analyses published in the literature

x

 

x

Provide consultation with researchers and decision makers about decision analysis methods, problems, and results

 

x

 

Understand and apply the concepts of public health and information sciences to clinical decision making and decision analysis

x

x

 

Communicate the results of decision analysis and other clinical research to decision makers, peers, and to the community through written and oral presentations and publications

 

x

 

Thoroughly understand the broad discipline of decision science including its theoretical underpinnings, its history of development, current applications, and areas of active inquiry

x

 

x

Advance the field of decision science through original research

 

 

x

 

Emphasis on Bioinformatics

Analyze high-throughput, biological data, such as microarrays, SNP chips, and mass spectrometer data, and understand the special statistical considerations that such data require

x

x

 

Retrieve and leverage various types of biological information from online repositories

x

x

 

Understand the basic biological principles that underlie our biological knowledge, and how the various forms of high-throughput data are used to address specific biological questions and expand our knowledge

x

 

x

Advance the field of statistics in bioinformatics through original research

 

 

x

 

*Key for demonstration (method):  QE   =    Qualifying examinations

                                                         SCP  =    Statistical consulting practicum

                                                         Dsrt  =    Dissertation


 The following are required for admission:

  1. Graduate application (see http://graduate.louisville.edu/apply) submitted to the School of Interdisciplinary and Graduate Studies (SIGS).
  2. Non-refundable application fee.
  3. At least two letters of recommendation written within past twelve months (can be submitted with form at http://graduate.louisville.edu/apply).
  4. Submission of GRE scores to the School of Interdisciplinary and Graduate Studies (85th percentile or better on Quantitative section is preferred).
  5. All post-secondary transcripts (may require foreign credential evaluation if not from accredited U.S. institution).
  6. Statement of goals submitted to the department office (must include desired academic and degree program).
  7. Foreign credential evaluation is required for each degree not from an accredited U.S. institution. This requirement may be waived, with approval by the dean, for degrees not considered to be relevant to evaluation of the applicant or whose transcript requires no foreign credential evaluation.
  8. A baccalaureate degree or its equivalent from an accredited institution is required for admission.
  9. A minimum undergraduate grade point average of 2.75 is required for unconditional admission.
  10. International students for whom English is not their primary language must show English language proficiency by one of:
  • Award of a degree from an accredited U.S. institution
  • Official TOEFL score of 100 or higher (iBT, or Internet-Based Test), 250 or higher (CBT, or Computer-Based Test), or 600 or higher (PBT, or Paper-Based Test)
  • Official documentation of passing the exit examination for the advanced level of the Intensive English as a Second Language Program at the University of Louisville


Curriculum


The curriculum consists of a minimum of 34 credit-hours of coursework and a doctoral dissertation. The student is eligible to sit for qualifying examinations upon completion of required coursework. Upon passing the qualifying examinations, the student enters candidacy to work on the dissertation. After the dissertation is submitted and approved, including an oral defense, the student is eligible to receive the Ph.D. degree in biostatistics.

Faculty Advisor

Upon admission to the Ph.D. program, each student is assigned to the graduate coordinator of the Ph.D. program for course advising. The graduate coordinator assumes the role of faculty advisor until the student chooses a dissertation advisor at which point this responsibility shifts to the dissertation advisor. If it becomes clear that a Ph.D. student will be working with a given faculty member prior to forming a dissertation committee, the student may request a change in course advisor by completing the form “Request to Change Academic Advisor.”

Program of Study

Upon admission to the Ph.D. program, a program of study is developed for each student by the faculty advisor and approved by the program director and department chair. Students who did not complete the M.S. program in biostatistics with the Department of Bioinformatics and Biostatistics may be required to complete additional coursework normally offered in the M.S. program. Decisions regarding additional coursework are made by the student’s assigned faculty advisor and such courses become part of the program of study. This approach gives maximum flexibility for addressing differing student qualifications and interests.

Degree Requirements

Completion of the coursework is the prelude to sitting for the qualifying examination. Successful completion of the qualifying examination allows the student to enter doctoral candidacy. A doctoral candidate must then develop and successfully defend a dissertation proposal that describes an original and independent research project. Upon successful defense of the proposal, a student may then proceed to continue dissertation research. Upon successful completion of the research, defense of the dissertation, and demonstration of the required competencies listed below, a student is awarded the Ph.D. degree.

The Ph.D. program in biostatistics is a 34 credit-hour program (minimum beyond a master’s degree) including the dissertation. Additional hours may be needed for completion of the program.

Coursework

     34 total credit-hours

     25 credit-hours of required coursework

       9 credit-hours of elective courses

Required Coursework

Emphasis (if any)

Course #

Course Title

Credit-Hours

All

PHST-710

Advanced Statistical Computing I

3

PHST-762

Advanced Statistical Inference

3

PHST-781

Advanced Linear Models

3

various

Electives

9

PHST-703

Doctoral Practicum in Consulting

1

Subtotal

19

 

No emphasis

PHST-691

Bayesian Statistics

3

PHST-724

Advanced Clinical Trials

3

PHST-780

Advanced Nonparametrics

3

PHST-782

Generalized Linear Models

3

PHST-783

Advanced Survival Analysis

3

Subtotal

15

 

Emphasis on decision science

PHDA-690

Utility Theory and Assessment

3

PHST-691

Bayesian Statistics

3

PHDA-701

Advanced Medical Decision Making

3

PHDA-663

Decision Analysis

3

PHDA-705

Statistical Methods for Cost-Effectiveness Analysis

3

Subtotal

15

 

Emphasis on bioinformatics

PHBI-751

High-Throughput Data Analysis

3

CECS-660

Introduction to Bioinformatics

3

BIOC-545

-OR-

MBIO-667

Advanced Biochemistry I

 

Graduate Cell Biology

3

 

3

PHBI-750

Statistics for Bioinformatics

3

PHBI-752

Statistical Genetics

3

Subtotal

15

 

Degree Total

34

 

The student may be required to take one or more prerequisite courses for a required course if the student does not meet the prerequisites. These prerequisite courses become part of the program of study but are in addition to the number of coursework credit-hours presented above.

Electives

The student must take electives from the following list. The student’s program of study specifies the particular courses to be taken.

Electives

Emphasis*

Course #

Course Title

Credit-Hours

--

D

B

x

x

 

PHBI-750

Statistics for Bioinformatics

3

x

x

 

PHBI-751

High-Throughput Data Analysis

3

x

x

x

PHST-682

Multivariate Analysis

3

x

x

x

PHST-711

Advanced Statistical Computing II

3

x

x

x

PHST-725

Design of Experiments

3

x

x

x

PHST-785

Nonlinear Regression

3

x

x

x

PHST-675

Independent Study in Biostatistics

1-3

x

x

 

PHBI-752

Statistical Genetics

3

x

 

 

PHDA-705

Statistical Methods for Cost-Effectiveness Analysis

3

 

x

 

PHST-724

Advanced Clinical Trials

3

 

x

x

PHST-782

Generalized Linear Models

3

 

 

x

PHST-691

Bayesian Statistics

3

 

 

x

PHST-780

Advanced Nonparametrics

3

x

x

x

PHST-704

Mixed Effect Models and Longitudinal Data Analysis

3

 

 

x

CECS-632

Data Mining

3

 

*Key for emphasis:   --    =    no emphasis

                                  D   =    emphasis on decision science

                                  B    =    emphasis on bioinformatics

The student may be required to take one or more prerequisite courses for an elective course if the student does not meet the prerequisites. These prerequisite courses become part of the program of study but are in addition to the number of coursework credit-hours presented above.

Qualifying Examination

Upon completion of the required coursework for the Ph.D. degree, a student is eligible to sit for the doctoral qualifying examinations. Each student must take two qualifying exams.

  • Exam 1 covers the following topics:
    • Statistical inference
    • Linear models
  • Exam 2 covers the following topics, depending on the student’s emphasis, if any:
    • No emphasis

       Student choice of any two of the following:

-          Statistical computing

-          Clinical trials

-          Generalized linear models

-          Survival analysis

    • Emphasis on decision Science

       Utility theory, assessment, and medical decision making

       Student choice of one of the following:

-          Bayesian analysis

-          Cost-effectiveness analysis

    • Emphasis on bioinformatics

       Statistical methods in bioinformatics (including high-throughput methods) and statistical genetics

       Student choice of one of the following:

-          Bayesian analysis

-          Statistical computing

Dissertation

In order to complete the degree, a candidate must submit and successfully defend a dissertation on a topic approved by his or her major professor and the dissertation committee. Dissertation work may be started following successful completion of doctoral qualifying examinations.

Dissertation Committee

The dissertation committee is formed by the candidate’s proposing a major professor (or principal advisor) and at least three other committee members. One member of the dissertation committee must be external to the Department of Bioinformatics and Biostatistics. The committee is appointed by the dean of the school upon the recommendation of the program director and chair of the department.

Dissertation Proposal (Pre-Dissertation Essay)

A dissertation proposal or pre-dissertation essay is submitted to the major professor and the dissertation committee. The proposal must be approved by a majority vote of the dissertation committee before the candidate undertakes further work on the dissertation.

The dissertation proposal is a typed document not exceeding 25 pages in length excluding topics (v) to (viii), below. The following formatting is used: Times New Roman 12-point font, margins of 1 inch on all sides and 1.5-line spacing throughout the body of the document. The School of Interdisciplinary and Graduate Studies dissertation guidelines for citing references must be followed. The document is divided into the following sections and in the following sequence:

(i)           Introduction and Literature Reviews – general introduction to the area of proposed research and relevant literature reviews

(ii)         Specific Aims and Significance – short section describing the specific aims of the proposed research and their potential importance in the field

(iii)       Preliminary Results – summary of the research findings the student already has (e.g., simulation results) towards one or more of the specific aims. This is an important component of the proposal that demonstrates the feasibility of the proposed research by the student.

(iv)       Research Plan – detailed description of the research towards the specific aims to be undertaken during the rest of the doctoral study period

(v)         References – complete references to all the cited literature. Journal names should not be abbreviated

(vi)       Tables – including table headings

(vii)     Figures – one figure per page

(viii)   Appendix – copies (in PDF format) of published articles and preprints that are most relevant to the proposed research

Dissertation Preparation

The dissertation is to be prepared in format and binding according to the guidelines established by the School of Interdisciplinary and Graduate Studies.

Dissertation Approval

The dissertation is submitted in completed form to the dissertation committee at least thirty days before the end of the term in which the candidate expects to be graduated. A candidate is not eligible for the final oral examination until the dissertation has been accepted by the committee.

The dissertation committee schedules an oral examination of the candidate. All faculty and students of the school are invited to attend the presentation portion. The defense is scheduled at the convenience of the members of the dissertation committee. The dissertation must be approved by the full committee.

Dissertation Distribution

One unbound copy of the dissertation, signed by the dissertation committee members, must be deposited with the School of Interdisciplinary and Graduate Studies before graduation. A copy of the final, signed dissertation must also be deposited with the department office.



Departmental Faculty


Guy Brock, Ph.D.

Associate Professor

Somnath Datta, Ph.D.

Professor

Susmita Datta, Ph.D.

Professor

Seongho Kim, Ph.D.

Assistant Professor

Maiying Kong, Ph.D.

Associate Professor

K.B. Kulasekera, Ph.D.

Professor and Chair

Doug Lorenz, Ph.D.

Assistant Professor

Rudolph S. Parrish, Ph.D.

Professor

Shesh Rai, Ph.D.

Associate Professor

Dongfeng Wu, Ph.D.

Associate Professor



Contact Information

Biostatistics-Decision Science - Ph.D.

Somnath Datta, Ph.D.
Program Director
(502)852-0081
susmita.datta@louisville.edu
 

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