MUSC Bulletin | College of Graduate Studies
Department of Biostatistics, Bioinformatics and Epidemiology
Requirements for Admission | Master of Science in Biomedical Sciences | Master of Science in Clinical Research | Doctor of Philosophy | Faculty Research Interests | Course Descriptions | Course Descriptions (MCR)
The Division of Biostatistics and Epidemiology conducts independent and collaborative research in biostatistics and epidemiology.
The graduate program in biostatistics provides in-depth training in statistical methods and their application in medical and health-related fields. Areas of particular emphasis are clinical trials, experimental design, categorical and longitudinal data analysis methods, and survival analysis.
The program in epidemiology emphasizes the identification and study of factors leading to disease and disability, with the ultimate goal of prevention and control. These factors affecting disease etiology include environmental exposures as well as life-style risks with possible genetic interactions. The research studies in epidemiology include health outcome data, and when possible, measurements of biological markers of exposure, effect and susceptibility. Areas of particular emphasis: cancer, cardiovascular, environmental health, genetics, perinatal, and oral health.
After mastering the basic concepts of biostatistics and epidemiology, the student becomes involved in quantitative design and analysis of clinical or basic science research, from which an independent research topic is selected for a thesis or dissertation project. Graduates from the division work in a variety of academic institutions, governmental agencies like the National Institutes of Health, the Centers for Disease Control, and the Environmental Protection Agency, or in pharmaceutical or health care industries.
Requirements for Admission
The Division of Biostatistics and Epidemiology offers graduate study leading to the Master’s of Science in Biomedical Sciences, or Doctor of Philosophy degree. Applicants must demonstrate an interest and aptitude in the development or application of quantitative techniques to problems in biomedicine. In addition to fulfilling general admissions guidelines of the College of Graduate Studies, students are encouraged to complete some undergraduate training in biology and mathematics. While a year of calculus and knowledge of linear algebra are very beneficial, they may, if deemed necessary, be taken at one of the local colleges, after admission to the Division of Biostatistics and Epidemiology.
Master of Science in Biomedical Sciences
The course program leading to this Master’s degree normally requires two years of full-time study. Graduation requirements include a minimum of 30 credit hours of didactic work, a successful qualification examination, and the completion of a thesis, which demonstrates the student’s mastery of biostatistical or epidemiological, methods in the analysis of a biomedical problem.
Doctor of Philosophy
In addition to core and elective course work, the student is expected to participate in the collaborative and teaching programs of the Division. Two examinations and a dissertation will demonstrate that the student has not only mastered the theoretical and applied aspects of biostatistics or epidemiology, but that s/he can apply the methods in a novel fashion to a relevant biomedical problem. The program includes 55 didactic credit hours, some of which are taken outside the division and some of which may transfer from a previous Master’s degree program.
Faculty Research Interests
Faculty research interests can be found on the web at www.musc.edu/dbe.
BMTRY-700. Biostatistics Methods I: Introduction to Clinical Biostatistics. This course introduces basic applied descriptive and inferential statistics. Topics include elementary probability concepts, an introduction to statistical distributions, point and interval estimation, hypothesis testing, and simple linear regression and correlation. Basic data management and analysis techniques will be introduced using the SAS system for personal computers. (includes 1 cr laboratory session) Prerequisites: College Algebra & at least one course in Calculus. (Required MS, PhD) 5 s.h.
BMTRY-701. Biostatistics Methods II: Regression Methods in Biology and Medicine. The objective of this course is to provide basic and intermediate skills necessary to apply regression methods to clinical and basic science research data. Topics include regression issues such as least squares estimation, hypothesis testing, diagnostics, model building and variable selection, and indicator variables. Simple and multiple linear regression, logistic regression, Poisson regression, and modeling of time-to-event (survival) data will be covered. The course uses a problem-based approach and applications to clinical and basic science problems are provided. Prerequisites: BMTRY 700. 4 s.h.
BMTRY-702. Biostatistics Methods III. The course covers a variety of intermediate level topics required to complete core competencies for analysis and interpretation of clinical and basic science data. The course emphasizes experimental designs employed in biological and medical research, including randomized block and nested designs, and factorial experiments. Longitudinal data methods including random and mixed effects models, and missing data methods are covered. Prerequisites: BMTRY 700, 710, 706, 707. 4 s.h.
BMTRY-704. Nonparametric Methods in Biology and Medicine. This course covers levels of measurements, order statistics, statistical methods for independent and correlated samples, distribution-free measures of association and testing. Students will identify situations where parametric techniques do not apply; to apply nonparametric methods for testing equality of variances; to test goodness of fit of data to a probability distribution; and to analyze one-and two-way layouts with nonparametric multiple comparisons. Prerequisites: BMTRY 700, 710. 3 s.h.
BMTRY-706 Theoretical Foundations of Statistics I. This course covers basic probability theory, random variables, transformation of random variables, expectation, moments and moment generating functions, discrete and continuous probability distribution functions; joint, marginal, and conditional distribution functions, bivariate normal distribution, and inequalities. Prerequisites: concurrent 700. 3 s.h.
BMTRY 707. Theoretical Foundations of Statistics II. This course is the continuation of Theoretical Foundations of Statistics I. Topics covered are order statistics, stochastic convergence, point and interval estimation, hypothesis testing, evaluation of estimates and tests, and asymptotic theory. Prerequisites: BMTRY 700, 706. 3 s.h.
BMTRY-711. Analysis of Categorical Data. This course offers a short review of standard measures of association and chi-square methods for binomial and multinomial distributions, followed by several special-purpose two-dimensional techniques. Other areas covered include the development of maximum likelihood-based inference (unconditional and conditional) for categorical data using generalized linear models. Models for binomial, multinomial and count data will be examined. In addition, topics including log-linear models, analysis of three-dimensional and higher tables, model selection strategies, regression model diagnostics, analysis of correlated or matched data, and generalized estimating equations, will be covered. Prerequisites: BMTRY 700, 706, 701. 3 s.h.
BMTRY-712. Sampling Methods in Biology and Medicine. This course emphasizes estimation of parameters of a finite population from samples drawn with and without replacement. Simple random samples, cluster and stratified samples, confidence intervals for parameters, ratio estimates, optimal allocation and required sample size are covered. Prerequisites: BMTRY 700, 706. 3 s.h.
BMTRY-713 Infectious Disease Epidemiology. This course provides an overview of infectious disease epidemiology with an emphasis on the application of epidemiologic techniques to a variety of diseases. Lectures, supplemented by video presentations and case studies provide the framework for the course. Prerequisite BMTRY 736 or permission of the instructor. Fall & Spring. 3 s.h.
BMTRY-714. Linear Models in Biology and Medicine. The matrix representation of the general linear statistical model is studied through the implication, distribution, and partitioning of quadratic forms and their probability distributions. Estimation of parameters in the linear model by methods of maximum likelihood and least squares will be presented along with the accuracy and precision of these estimators. Estimability in both the full rank and less than full rank models is introduced. The test statistic for the general linear hypothesis is derived, and its distribution is determined under an assumption of normally distributed errors for both the null and a general alternative hypothesis. Sufficient examples are given to show its application to tests on means as well as in ANOVA and ANOCOVA. Students prepared in basic statistical methods and theory, and matrix algebra are eligible to take this course. Prerequisites: BMTRY 700, 706, 707, 710. 3 s.h.
BMTRY-718. Stochastic Processes in Biology and Medicine. An overview of the role of stochastic processes is followed by review and extension of probability theory, including probability generating functions. The course will cover stochastic processes like random walk, branching processes, Markov processes, renewal theory, and hidden Markov process. Applications of these processes in genetics, clinical trial design and data analyses, and computer simulations are discussed throughout the course. Prerequisites: BMTRY 700, 706, 3 s.h.
BMTRY-719. Bayesian Biostatistics. It is a graduate course on effective and sophisticated approaches to Bayesian modeling and computation in biostatistics and related fields. The course begins with a gentle introduction of Bayesian inference starting from first principle, but it intends to cover the philosophical backgrounds, logical developments and computational tools associated with Bayesian. Prerequisites: 700, 706, 707, 710. 3 s.h.
BMTRY-721. Fundamentals of Statistical and Epidemiological Collaboration. Required for all students with emphasis in biostatistics and epidemiology prior to obtaining a masters degree. Teaches students how to participate in collaborative research including methods for sample size estimation, preparation of plans for statistical analysis and of analytic reports. Those students in the Ph.D. program who do not have previous collaborative working experience and/or training would also be required to take this course. Prerequisites: 700, 710, 736. 2 s.h.
BMTRY-722. Analysis of Survival Data. This is an introductory course in theory and application of analytic methods for time-to-event data. The methods covered include nonparametric, parametric, and semi-parametric (Cox model) approaches. The topics covered will also include types of censoring and truncation, sample size and power estimation, and a brief introduction to counting process method. Extensive use of SAS procedures for survival analysis is incorporated into the course. Prerequisites: BMTRY 700, 706, 710, and working knowledge of SAS. 3 s.h.
BMTRY-723. Applied Biostatistics. This course provides a survey of descriptive and inferential statistics commonly used in biomedical research. This course is intended for graduate students in other Basic Science departments and Colleges, clinical residents/fellows, and medical and dental students who seek a working knowledge of biostatistical methods and their applications. Topics include measures of central tendency and variation, frequency distributions, confidence interval estimation, comparison of means and proportions, sample size calculation, simple linear regression and correlation, overview of multiple regression and regression diagnostics, one and two way analysis of variance, chi-square tests, common nonparametric procedures, and an introduction to basic principles of experimental design (completely random and randomized block experimental designs, factorial and repeated measures experiments). Students are expected to be able to design simple experiments, to identify and carry out an appropriate statistical analysis, and to interpret results through statements of both statistical and clinical conclusions. Students also receive instruction in the use of a statistical software package. 3 s.h..
BMTRY-724. Design and Conduct of Clinical Trials.This is a comprehensive course providing an overview in the design and conduct of clinical trials. The course covers the types of clinical trials; study design (including sample size estimation); randomization methods and implementation; project and data management; ethics; and issues in data analysis (e.g., intent-to-treat; handling of missing data ; interim analyses). The course is designed primarily for the students in the Department of Biostatistics, Bioinformatics, and Epidemiology; however, both clinical and basic science investigators can benefit from this course provided they have the required background in basic statistics. Prerequisites: BMTRY 700. 3 s.h.
BMTRY-725. Grant Development for Clinical Research. This course is required for participants in the Clinical Masters program and Ph.D. students in the Department of Biometry and Epidemiology. The objective of the course is to prepare a grant application (R03, F31, K-award, etc.) for submission to a funding agency. Students learn grantsmanship, develop the sections of a grant (aims, background, preliminary studies, methods), learn about IRB regulations and procedures, about ethics, and develop an IRB application. They also develop a research budget. Students will be given examples of successful grants and grants that have not been funded to discuss. This is a pass/fail course. Students should come to the course with a research idea that can be developed into a grant and, if possible, with preliminary data. Semesters taught: Fall and Spring. Prerequisites: 700, 710, 736 or permission of instructor. 2 s.h.
BMTRY-726. Multivariate Methods in Biology and Medicine. This course will consist of multivariate techniques in biology and medicine including multivariate tests of mean vectors and covariance matrices, multivariate analysis of variance and regression, repeated measures analysis, random and mixed effects models, generalized estimating equations, generalized linear mixed models, canonical correlation, factor analysis, principal components analysis, discriminant analysis. Directed to biostatistics students; useful for epidemiology students. Prerequisites: BMTRY 702, 706, 710, Knowledge of Matrix Algebra & SAS. 2 s.h.
BMTRY-734. Cancer Epidemiology. This survey course will introduce students to the major cancer risk factors. For the major cancers the most important epidemiological studies will be reviewed. The issue of genetic susceptibility and the use of biomarkers in cancer epidemiology will be studied as well as cancer screening. Prerequisites: BMTRY 736 or permission of the instructor. 3 s.h.
BMTRY-735. Perinatal Epidemiology. This course will explore the epidemiologic determinants of adverse pregnancy outcomes. Topics include: data sources for research in perinatal health; federal and state programs designed to improve pregnancy outcomes; funding sources for research and demonstration programs in perinatal health; identification and measurement of maternal socio-demographic and clinical risk factors for adverse pregnancy outcomes; teratogenic and mutagenic factors; fetal, perinatal, neonatal, and infant mortality; prematurity and low birth weight; neonatal assessments of growth and development; and maternal and neonatal morbidity. Additional topics include perinatal health services research, conducting needs assessments, program evaluation, and systems evaluation. Prerequisites: BMTRY 736. 3 s.h.
BMTRY-736. Foundations of Epidemiology (Epidemiology I). This course provides an introduction to basic epidemiologic principles including measurements of disease occurrence, study designs (cohort, case-control, randomized clinical trials) and calculation of risk. Lecture material is supplemented with exercises and discussion of examples from the epidemiologic literature and presentations of epidemiologic studies by guest speakers. Prerequisites: None. (Required MS and PhD). 3 s.h.
BMTRY-737. Epidemiology of Cardiovascular Diseases. This is an advanced course designed to acquaint students with the use of epidemiology in the study and investigation of cardiovascular diseases. Prerequisites: BMTRY 736 or permission of instructor. 3 s.h.
BMTRY-738. Design and Conduct of Epidemiologic Studies. An emphasis will be placed on procedures used in the implementation of epidemiological research studies. Prerequisites: BMTRY 736 or permission of instructor. 3 s.h.
BMTRY-747. Foundations of Epidemiology II. This course will provide a comprehensive and quantitative view of the design, conduct, analysis, and interpretation of epidemiological studies and use of EGRET software. There is a more in-depth coverage of topics than in Epi I. Prerequisites: BMTRY 700, 710 concurrently. 3 s.h.
BMTRY-748. Foundations of Epidemiology III. This course will provide an in-depth quantitative view of advanced statistical analysis of epidemiological studies. The use of epidemiological analysis software (Epicure) will be taught. Builds on techniques developed in Epi II. Prerequisites: BMTRY 700, 710, 747. 3 s.h.
BMTRY-763. Spatial Epidemiology-Statistical Methods & Appl. This course focuses on the basic epidemilogical and statistical issues to be found int he study of the spatial/geographical distribution of disease. The topics of disease mapping, disease clustering and ecological analysis will be examined. Prerequisites: BMTRY 701. 3 s.h.
BMTRY-764. Statistical Computing for Research. Student learn to use the primary statistical software packages (SAS, R, Stata), principles of data management, and scientific document preparation. Prerequisites: BMTRY 700. 3 s.h.
BMTRY-767. Statistical Methods for Clinical Trials. This course is intended mainly for MS and PhD students in DBE interested in the statistical methods and issues arising in a variety of clinical trials. The course will include topics in adaptive/flexible study design, adaptive randomization, sample size estimation, missing data handling, interim analysis methods, and issues in data analysis. The course will also cover topics related to the statistician's role in clinical trials, including the presentation of statistical information and statistical monitoring of safety data. At the completion of the course, students will have the tools to collaborate with clinicians in the design and implementation of clinical trials as well as analysis of study data, and will have developed their skills in being more critical readers of the medical literature. Prerequisites: BMTRY 700, 701, 702, 722, 724. 2 s.h.
MCR-700. Clinical Biostatistics. This course is intended to develop an informed consumer of biostatistics rather than an independent analyst. Students in this course will utilize problem solving applications that demonstrate the students' understanding of the use of specific biostatistical tools. By conclusion of the course, students will be able to: 1) Understand the characteristics associated with different types of statistical tests. 2) Interpret study results that use t-test, chi-square, regression, and other statistical tests and tools. 3) Evaluate and determine the best statistical approach for clinical research. 4) Develop comprehensive analytic plans to address an array of clinical and translational applications.3 s.h.
MCR-724. Intro to Clinical Trials. This is a comprehensive course in the design and conduct of clinical trials. The course covers the types of clinical trials; study design (including sample size estimation); randomization methods and implementation; project and data management; ethics; and issues in data analysis (e.g. intent-to-treat; missing data analysis). Both clinical and basic science investigators can benefit from this course provided they have the required background in statistics.3 s.h.
MCR-725. Grant Development. The course is required for participants in the Clinical Masters Program and Ph.D students in the Department of Biometry and Epidemiology. The objective of the course is to prepare the student to develop a draft grant application by teaching them about grantsmanship, helping them to develop the sections of a grant(alms, background, preliminary studies, methods), teaching them about IRB regulations and procedures, about ethics, and about developing a research budget. Students will be given examples of successful grants and grants that have not been funded to discuss and critique. 2 s.h.
MCR-731. Critical Review. This course is required for the Master of Science in Clinical Research. It is assumed that students in this class have a solid foundation in research design and both parametric and nonparametric statistics. An emphasis will e placed on the competencies and processes necessary to review the scientific literature. In particular, the students will review the published and unpublished literature associated with clinical research results. The focus of the class will be the review of the types of scientific and clinical research manuscripts, papers, and reports produced from different study approaches. The course will identify resources for the critical review of the scientific literature. The considerations and criteria for critical review of the literature will be addressed in the course. Students will prepare written critiques of selected literature and manuscripts. Prerequisites: MCR 700, 736, or permission. 2 s.h.
MCR-732. Comparative Effectiveness Research. The American Recovery and Reinvestment Act of 2009 (ARRA) set aside a large amount of funding for comparative Effectiveness Research (CER). This type of research is not new, it has been evolving over the last 20 years under several names. CER studies are sometimes described as "Clinical Epidemiology", "Technology Assessment", "Cost Effectiveness Analysis", "Outcomes Research", "Patient-centered Research" or "Evidence-based Medicine". The Congressional Budget Office (2007) defined CER as: "rigorous evaluation of the impact of different options that are available for treating a given medical condition for a particular set of patients" (CBO, 2007 p.3). A recent Institute of Medicine (IOM, 2009) list of CER topics for priority funding identify 4 types of designs: 1) Systematic Review; 2) Database Review; 3) Prospective Observational Study; and 4) Randomized Clinical Trial. The IOM defines CER as follows:
CER is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or 10 improve the delivery of care. The purpose of CER is to assist consumers, clinicians, purchasers, and policy makers to make informed decisions that will improve health care at both the individual and population levels.
This course is focused on design and measurement issues for three of the four types of study designs: 1) Systematic Review; 2) Database Review; 3) Prospective Observational Study. (The issue of design of the Randomized Clinical Trial is covered in a separate course.) This course will also cover the approaches used for interpretation and translation of CER data through decision models to compare the cost effectiveness of treatments. Decision analysis models are predictive mathematical models that are used to structure CER and cost data to help inform evidence-based decision choices. The following topics are include in the course: 1)a review of research designs and statistical methods for outcomes research, 2)measurement of efficacy, effectiveness, opportunity cost, and quality of life, 3)benchmarks for economic value, cost effectiveness, cost utility, and budget impact, 4)mathematical approaches for estimating expected outcomes: decision trees, Markov and simulation/estimation with regression. The course is designed for clinical researchers who have an identified area of interest in medical condition or a treatment approach. Most course assignments require the student to have a clinical focus area to which they can apply the course topics and designs. The design and construction of a decision model in an area of interest to the individual student is required.1-3 s.h.
MCR-733. Health Services Research. This course is designed to introduce conceptual models and theory from sociology, health behavior, economics, organizational theory, and political science and illustrate their use in the design of health care research studies. 3 s.h.
MCR-736. Clinical Epidemiology. This course is intended to focus on issues unique to the application of epidemiological principles in the clinical and translational research arena. The emphasis of this course will be patient oriented populations. By the conclusion of the course, students will be able to: 1) Understand the characteristics associated with different study methods. 2) Understand the components of the scientific process model and apply it to their clinical and translational studies. 3) Design and develop a study of protocol and study proposal. 4) Develop comprehensive analytic plans to address an array of clinical and translational studies. 3 s.h.
MCR-738. Clinical Research Intro. The purpose of this course is to expose students to several types of Clinical and Translational Research. To provide the student with the basic structure of clinical research available throughout the campus. Emphasis will be placed on the variety of clinical research being conducted on MUSC's campus.1 s.h.
MCR-740. Clinical Research Methods. The course will focus on the components and principles of clinical and translational research. The steps used in formulating questions, study design, hypothesis generation, data analysis plan, human subjects protection, study significance, and expected results. The course will introduce these components with participants organizing their research in standard, comprehensive format.2 s.h.
MCR-742. Intro to Molecular Medicine. Students will learn about the following: basics of bioinformatics, proteomics, clinical cytogenetics, cell and vaccine therapy, DNA microarrays, fiviRi, 64 slice CT, regenerative medicine, and zebra fish facility. Students will learn the theory behind each of the technologies and will receive practical exposure to them. Students are encouraged to incorporate a component of molecular medicine into their poster/research project based on the skills obtained over the six week program.2 s.h.
MCR-744. Molecular Approaches to Experimental Medicine. This course is intended to address fundamental processes that contribute to human disease by providing students with a basic understanding of the cell and molecular basis for disease; familiarity with relevant recent experimental literature; and an awareness of unmet needs.4 s.h.
MCR-746. Data Management for Clinical Research. This course is intended to introduce clinical researchers to research oriented data management and related basic topics in informatics. Students taking this course will learn about basic concepts in relational database design, modern research data capture tools, clinical data warehousing, security risks and mitigations, privacy issues in electronic data, data standards, data mining, and other related topics. 2 s.h.
MCR-748. Data Management for Clinical Research. This course is intended to introduce clinical researchers to research oriented data management and related basic topics in informatics. Students taking this course will learn about basic concepts in relational database design, modern research data capture tools, clinical data warehousing, security risks and mitigations, privacy issues in electronic data, data standards, data mining, and other related topics. 2 s.h.
MCR-750. Ethical Issues in Clinical Research I. An emphasis will be placed on the ethical issues associated with clinical research and practice. The focus of the class will be the review of the competencies involved in the conduct of ethically responsible research, the process of assessing ethical issues in research and study will be described. The ethical considerations in study designs, study implementation, data management, data analysis, data interpretation and results presentation and publication will be described. 1.0 s.h.
MCR-789. Special Topics. Special Topics course developed by student and mentor on a specific topic in their research area or grant topic. 1-3 s.h.
MCR-970. Research. Research hours for students to work on research, projects, thesis, and/or grant proposal. 1-10 s.h.
|Last updated:||November 28, 2012 2:48 PM|