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Course Descriptions

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]

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]

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: 8311: Epidemiologic Theory and Methods I. [4]

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]

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 Students work in small groups to write and critique published and unpublished manuscripts, with a focus on understanding the essential components of a scientific manuscript or presentation, as well as the process of publishing in the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.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. [2]

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]

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]

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]

These methods electives will be taught in modular format, most often with three modules on related quantitative methods topics, which will vary annually. Students will explore enhanced study design and advanced analytic methods in epidemiology like quantitative bias analysis, double-sampling and computational methods to handle missing data, causal mediation analysis, meta-analysis, propensity score methods, network analysis, spatial analysis, and simulation. Exercises with provided datasets and the student's own data will be included. May be repeated. [1-3]

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]

This course is designed to provide students with the foundation necessary to critically assess research protocols and published literature on the inclusion and omission of sex and/or gender. This course will also provide understanding of the biological mechanisms involved in sex as a biological variable and will investigate the differences and relationship between sex and gender. Topics discussed include: basic definitions and measurements of sex and gender, biological and sociological contributions to sex and gender, review of sex chromosomes, health disparities and ethical implications, and study designs and statistical assessment of sex and/or gender in research. Examples are stressed with reference to assumptions and limitations. [2]

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.

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]

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.

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

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.

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]

Research prior to entry into candidacy (completion of Qualifying Examination). [0-12]

Research after candidacy. [0-12]