Course Descriptions

8310. Causal Inference. This course will concentrate on conceptually grasping tools of logic and critical thinking as they apply to epidemiologic research. Our emphasis will be on rigorous definition of a causal effect and the minimal conditions necessary to consistently estimate such effects. In a small group format, we will examine case studies and anchor our discussions in readings from philosophy of science, logic, and probability. We will cover examples of valid and fallacious arguments, probability calculus, probabilistic fallacies, applications of Bayes theorem, the frequentist and Bayesian perspective, counterfactual logic, introduction of directed acyclic graphs (DAG), and interpretation of p-values and confidence intervals in epidemiologic research. [3] K. Hartmann

8311. Epidemiologic Theory and Methods I. This is the first of a two-course series on advanced epidemiologic concepts and methods that includes measures of disease frequency, measures of effect, descriptive epidemiology, study designs, bias, misclassification and effect measure modification, and ethics in epidemiologic research. A case-based approach will engage students in demonstrating concepts using actual research data and in critical appraisal of case studies and publications that feature strong and weak examples. [4] E. Kabagambe

8312. Epidemiologic Theory and Methods II. This second in a two-course series provides an in-depth treatment of concepts and skills in epidemiologic research, including problem conceptualization, study design, data analysis and interpretation. Includes emphasis on how to design studies to best measure etiologic effects and includes advanced discussion of confounding, interaction, and missing data. A continued case-based approach will engage students in demonstrating concepts and methods using the students’ own data. Prerequisite: 311: Epidemiologic Theory and Methods I. [4] A. Kipp

8314. Modern Regression Analysis. This is the second in a two course series designed for students who seek to develop skills in Biostatistical reasoning and data analysis. Students learn modern regression analysis and modeling building techniques from an applied perspective. Theoretical principles will be demonstrated with real world examples from biomedical studies. This course requires substantial statistical computing in software packages STATA and R; familiarity with these packages is required. Topics include modeling for continuous outcomes such Simple linear regression, Multiple linear regression, Analysis of Variance (ANOVA: one-way, two-way, three-way, analysis of covariance) and modeling of additional outcomes such as binary response, survival time, and count data (logistic regression, cox proportional hazard model, and Poisson/negative binomial regression, respectively). Also covered are regression diagnostics, Splines, data reduction techniques, model validation, and Parametric bootstrapping, and methods for missing data will be introduced. Prerequisite: Principles of Biostatistics or equivalent; familiarity with STATA and R software packages. [4]

8315. Scientific Writing I. Participatory course in which students develop skills in presenting research results in manuscripts, abstracts, and posters. Students work in small groups to write and critique published and unpublished manuscripts, with a focus on understanding the essential components of a scientific manuscript or presentation, as well as the process of publishing in the peer-reviewed literature and managing reviewer and editor comments and requests. [1] 316. Research Ethics. This course is designed to guide students through the initial stage of formulating an epidemiologic research topic and plan, prior to the development of a full research proposal. [1] M. Epplein

8321. Applied Epidemiologic Methods in Regression: Binary Data. Concepts and applications, including logistic regression, binomial regression, ordinal regression, multinomial regression, quantile regression, model building strategy, additive and multiplicative interaction, clustered and longitudinal data, and graphical exploration. Includes computer-based experience with real data. [4] A. Beeghly-Fadiel, M. Sanderson, N. Jimenez-Truque

8323. Epidemiologic Methods: Design and Analysis with Time-to-Event Data. Concepts and applications in survival analysis and analysis of incidence rates, including truncation and censoring, life tables, nonparametric approaches (e.g. Kaplan-Meier, log-rank), semi-parametric approaches (e.g. Cox models, proportional hazards regression), parametric approaches (e.g. Weibull, gamma regression) accommodating time-dependent exposures, Poisson regression, sensitivity analysis, bootstrapping, and multiple imputation. [4] C. Slaughter

8325. Scientific Writing II – Proposal Development in Epidemiology. Participatory course in which each student develops a high quality, detailed research proposal suitable for submission to NIH or AHRQ that includes both a technical proposal and a draft budget justification. Includes lecture, in-class exercises and group processes. [2] K. Hartmann

8331. Seminar in Quantitative Methods and Measurement. Concepts and application of cross-cutting tools used for unique and/or specialized types of measurement and instrument development for areas such as physical activity, clinical laboratory tests, and imaging studies. [2] May be repeated. K. Archer

8332. Advanced Methods for Epidemiology. These methods electives will be taught in modular format, most often with three modules on related methods topics, which will vary annually. Students will explore methodological issues in epidemiology like measurement error, missing data, intermediate variables, complex study designs, meta-analysis, splines, propensity scores, simulation. Exercises with provided datasets and the student’s own data will be included. [1] May be repeated. 

8333. Analytic Techniques for Genetic Epidemiology. This course will take an example-based approach to provide students with the skills necessary to conduct statistical association analysis of genetic data from human populations for genetic epidemiology studies. Topics will include quality control, statistical methods for association testing, common study design issues, future directions of genetic epidemiology and advanced topics. [3] T. EdwardsD. Velez Edwards

8340. Content Area Intensives. These intensives are offered on a rotating basis and taught by faculty with research expertise in the content area of focus. Areas of epidemiology may include cancer, cardiovascular disease, child health, chronic disease/diabetes, genetics, global health, health care, infectious disease, nutrition, pharmacoepidemiology, reproductive, and social. [1-4] May be repeated.

8356. Clinical Trials. Systematic overview of principles in design, implementation, and analysis of clinical trials. Emphasis on applications in chronic disease epidemiology. In-depth details of case examples from cardiovascular disease and cancer treatment and prevention trials will be covered.

8357. Decision Analysis and Cost Effectiveness. Overview and practice of conducting decision analysis, including cost effectiveness in epidemiologic research and to the translation and utility of epidemiologic data.

8358. Molecular Techniques for Public Health Research. This course presents an introduction to the principles of the molecular techniques used in epidemiologic investigations. Emphasis will be on the development of a general understanding of the techniques and vocabulary necessary to communicate with researchers and laboratory personnel involved in the study of disease both at the individual and population level.

8359. Event Surveillance and Mathematical Modeling of Dispersion. Overview and practice of event surveillance and mathematical modeling for a variety of research areas, including infectious disease and environmental epidemiology.

8360. Advanced Predictive Modeling and Simulation. Exploration of the underlying philosophy and approach to predictive modeling. Includes practical experience in developing predictive models and simulations, including measures of fit, statistical approaches to building and comparing models, and approaches to best reporting the results and implications of such methods.

8370. Current Topics in Research. Students attend weekly presentations selected from the Vanderbilt Epidemiology Center Seminar Series, Biostatistics Clinic, clinical grand rounds on topics related to content area interests, and other relevant seminars. Students will convene with faculty to reflect on and critique components of research presentations relevant to the students’ interest and to the contemporaneous topics being covered in the core epidemiology curriculum. Course assignments will focus on critical appraisal of a methodologic challenge identified in a seminar setting that has immediate relevance to the student’s own research. [1] May be repeated X. Zhang

8371. Special Topics Seminar in Epidemiology. Faculty offer small groups of students a study course on a topic of mutual interest and concern in the faculty member’s area of expertise. [1-3] May be repeated.

8372. Advanced Readings in Epidemiology. Additional readings in specialized epidemiologic topics will be explored in depth under the guidance of a faculty member. [1-3] May be repeated.

8373. Independent Study in Epidemiology. Designed to allow the student an opportunity to master advanced skills in epidemiology while pursuing special projects under individual members of the faculty in their areas of expertise. [1-3] May be repeated .

8374. Advanced Readings in Epidemiologic Context, Thought, and History. Reading and discussion of seminal literature in the history of epidemiology as well as contemporary literature that provides social and cultural context for the development of the field, challenges to the application of epidemiologic findings, consideration of roles and history of public health advocacy, and exploration of topics like social justice and research ethics through the lens of fiction, non-fiction, and scientific literature. A core reading will be selected to launch each semester and students will work as a group to select the balance of the readings for the semester from a recommended source list. Discussions will be facilitated by faculty and students including guest lecturers. Minimum of masters training in quantitative discipline and research experience in epidemiology or related field is required; other graduate students with permission of the instructor. [2] M. Aldrich

Assigned by the Graduate School 
8999. Non-candidate Research. Research prior to entry into candidacy (completion of Qualifying Examination) and for special non-degree students. [Variable credit: 0-12]

9999. Ph.D. Dissertation Research

Optional Human Genetics Courses 
Recommended Human Genetics course sequence for Epidemiology PhD students

Spring of 1st year: HGEN 330 (Special Topics in Human Genetics) OR Fall 2nd year: HGEN 340 (Human Genetics I)

Spring of 2nd year: MPB 341 (Human Genetics II), requires permission from instructor and received an A in HGEN 330 or has passed HGEN 340

Fall of 3rd year: EPI 333 (Analytical Techniques for Genetic Epidemiology)

Optional: Spring of 3rd year: HGEN 390 (Genetic Epidemiology)


Feel free to contact with any questions.