Courses by Topic
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- *Designing Clinical Research (EPI 150.03 and EPI 202)
These courses provide instruction in developing a clinical research question and creating a concise protocol that includes literature review, study design, subject sampling and recruitment, instruments and other measurement approaches, sample size, consent form, budget and timetable. Each trainee reviews and supports the work of colleagues. The course closely follows the textbook Designing Clinical Research, by S. Hulley and other TICR faculty, now in its third edition.
EPI 150.03 is intended for undergraduate and professional students as well as clinical residents. EPI 202 is intended for doctoral students, fellows, or faculty members.
- *Epidemiologic Methods
Instruction in the diverse array of study designs, and their theoretical interrelatedness, available in clinical and epidemiologic research; importance of measurement; different types of measures of disease occurrence; methods to measure exposure - disease association; measures of attributable risk; effect-measure modification; approaches to identify and minimize selection, measurement and confounding bias; and conceptual motivation for more sophisticated methods (e.g., regression or marginal structural approaches) to manage confounding, which are increasingly common tools in epidemiologic analyses.
- *Clinical Epidemiology
Instruction in the research implications of evidence-based clinical medicine, including the specifications of diagnostic tests, screening tests, and prognostic tests.
- Clinical Trials
Instruction in experimental study design options; methods of randomization; blinding, interventions and controls; measuring outcomes and adverse effects; follow-up, compliance and postrandomization problems; ethical issues; and working with pharmaceutical companies.
- Epidemiologic Methods II (EPI 207)
Instruction in the interrelationships between various measures of disease occurrence and association; concepts of attributable risk; interactions; practical and theoretical considerations of the most common study designs in observational research; methods of reducing confounding including matching, instrumental variables and propensity scores.
- Systematic Reviews (EPI 214)
Instruction in the methods of systematic and unbiased identification of primary research studies; abstraction of data; determination of summary estimates and evaluation of heterogeneity.
- Measurement Theory and Practice (EPI 228)
Instruction in how to find and evaluate existing measurements, in terms of validity and reliability, for given health-related constructs; how to begin to develop and validate new measurements when there are no sufficient existing ones; and how to implement prospective measurement in practical field research, including procedure documentation, questionnaire administration, physical examination, and biological specimen collection.
- Epidemiologic Methods III (EPI 265)
This course will focus on clearly articulating and testing research hypotheses related to the determinants and consequences of chronic conditions. Each session will introduce specific methodological concepts for epidemiologic studies, organized around an illustrative applied research paper. The course will emphasize causal inference from observational data. Most examples will be drawn from literature on social and lifecourse determinants of dementia, stroke, and cardiometabolic disease.
- Mathematical Modeling of Infectious Diseases (EPI 266)
Introduction to concepts of mathematical modeling of infectious diseases; topics include branching processes and the basic reproduction number, dynamical systems, and methods for data fitting including Markov chain Monte Carlo.
- Econometric Methods for Causal Inference (EPI 268)
Instruction on estimating the causal effects of health-related policies, programs, and interventions using observational data and methods developed in the field of econometrics. Topics include difference-in-differences, instrumental variables, and regression discontinuity.
- *Biostatistical Methods for Clinical Research
I (BIOSTAT 200)
Introduction to descriptive statistics, distributions, probabability, exploratory data analysis, and selected variable parametric and non-parametric inference. The Stata software package will be used throughout to implement concepts learned in class and to allow scholars to begin to explore their own data.
Opportunities and Challenges of Complex Biomedical Data: Introduction to the Science of "Big Data" (BIOSTAT 202)
Introduction to the opportunities and challenges of using biological and health-related "big data" to perform biomedical research.
- Biostatistical Methods for Clinical Research
II (BIOSTAT 208)
Instruction in multiple predictor analyses as a tool for control of confounding and for constructing predictive models. Topics will include linear regression and logistic regression. The Stata statistical package will be used throughout.
- Biostatistical Methods for Clinical Research
III (BIOSTAT 209)
A continuation of the Winter Quarter course in multivariable statistical analysis that includes instruction in survival analysis and analysis of repeated measures and clustered data. The course culminates with student presentations of statistical analyses of their own research projects.
- Biostatistical Methods for Clinical Research
IV (BIOSTAT 210)
A continuation in the biostatistics for clinical research sequence, covering advanced methods for building and evaluating regression models. The emphasis is on methods which cut across common families of regression models in biostatistics: predictor selection, model diagnostics, and missing data. The statistics package Stata will be used throughout the course.
- Biostatistical Methods V: Statistical Issues in Design, Monitoring, and Analysis of Randomized Controlled Trials (BIOSTAT 226)
Instruction in advanced topics in the design, monitoring and analysis of randomized clinical trials.
- Advanced Approaches to the Analysis of Observational Data (BIOSTAT 215)
A common goal of observational clinical or epidemiologic research is to estimate the causal effect of particular exposures or interventions on some health outcome. This course will describe more advanced methods that may succeed in estimating causal effects in cases where standard approaches break down.
- Machine Learning in R for the Biomedical Sciences:
Methods for Prediction, Pattern Recognition, and Data Reduction
This course will provide an introduction to use of machine learning (automated statistical algorithms applied to complex data structures) to solve problems of prediction, pattern recognition, and data reduction in various fields related to biomedical research; the R software environment will be used throughout.
|Data Capture & Software Manipulation
*Database Management Systems for Clinical
Research (EPI 218)
Instruction in choosing the appropriate data management system; design of research databases; options in data entry; form and report generation; computer security; and budgeting for data management personnel and equipment.
- *Introduction to Statistical Computing in
Clinical Research (BIOSTAT
212) Instruction in use of statistical software for exploring and analyzing clinical research data. While the roles of spreadsheet and relational database programs will be discussed, the course will focus on the Stata statistical software package for analyzing and presenting data.
- Introduction to Computing in the R Software Environment
Instruction in how to use the R computer software program for data description, analysis, graphical presentation, and programming. Topics include how to import data files into R; assign objects in R and identify R object types; manipulate data objects in R; conduct basic statistical analysis in R, including generation of graphs and tables; write functions in R and iteratively apply R code and functions; generate reports using R Markdown; and become prepared to take additional advanced courses in data analysis which require computation and programming in R.
|Genetic Epidemiologic Methods
- Molecular and Genetic Epidemiology I
Introduction to the concepts, principles, and use of molecular and genetic methods in epidemiologic and clinical research and how to develop a framework for interpreting, assessing, and incorporating molecular and genetic measures in research.
- Cost-Effectiveness Analysis in Medicine and Public Health (EPI 213)
Instruction in creating decision trees; obtaining input values for probabilities, utilities, and costs; and calculating health, cost and cost-effectiveness outcomes. Course participants will design and complete their own decision and cost effectiveness analyses using customized software.
- Epidemiologic Approaches to Implementation Science (EPI 239)
An introduction to implementation science taught using the language and framework of epidemiologic methods. Instruction is provided in the objectives of and motivation for implementation science (e.g., gaps in implementation and interventions to reduce them); typical study designs used in implementation science; common measurements (especially outcome measurements); intervention schemes; means to enhance causal inference; and approaches to garner research funding. Methods from various social sciences (e.g., mixed methods) are also covered.
- Program Evaluation in Clinical and Public Health Settings (EPI 242)
Instruction in different types of program evaluation, including needs assessment, formative research, process evaluation, monitoring of outputs and outcomes and impact assessment; developing an evaluation plan and using systematically collected information about a program to understand whether and how the program is meeting its stated goals and objectives; improve program effectiveness; make decisions about future programming.
- Human Centered Design (EPI 243)
Instruction in the process of human-centered design as it applies to developing solutions for problems faced by anyone involved in the healthcare delivery system (patients, family and friends of patients, caregivers, and administrators).
- Introduction to Implementation Science
Theory and Design (EPI 245)
An introduction to the different target audiences and approaches needed to translate biomedical evidence into practice. The course is the gateway for scholars who plan for additional study within this discipline but also suffices as cross-exposure for scholars from other disciplines. In addition to didactic work, scholars are guided through the creation of a research protocol aimed towards translating their particular choice of evidence into practice.
- Translating Evidence Into Practice: Individual-Centered
Implementation Strategies (EPI 246)
Instruction in developing interventions for individual health behavior change, including behavior change strategies at the individual, interpersonal, and system/community level; developing practical frameworks to integrate principles of behavior change theory.
- Designing Interventions to Change Organizational Behavior (EPI 247)
Instruction in translational tools at the health care system level to promote the adoption of evidence-based medicine by the public and providers through mechanisms that influence health care delivery systems.
- Community Engaged Research (EPI 248)
Introduces the principles and applied methods of community engaged research, including defining the community and partnership models for identifying relevant research questions, developing and implementing study designs, interpreting and disseminating findings, and scaling-up studies for translational implementation research.
- Translating Evidence Into Policy: Framing Research to Influence Policy
Instruction in the policy process and strategies for collecting and disseminating research findings to inform and influence that process. The course will be taught through a series of lectures and interactive sessions during which trainees will have an opportunity to apply the strategies to their own work.
- Publishing and Presenting Research (EPI
Instruction in preparing abstracts, posters, all aspects of manuscripts, and oral presentations.
- TICR Program Seminar for First-Year Masterís and Certificate Program Scholars (EPI 220/230)
Biweekly seminar for first year students to present their research to their colleagues and faculty.
- Masters Seminar II Winter (EPI 221)
Biweekly seminar for second year students to present their projects and specialized methodologic topics.
- Grant Writing Workshop (EPI 258)
This course is designed to clarify early investigators’ research and career goals and to learn all the components of NIH pre- and post-doctoral grants.
- Advanced Grant Writing Workshop (EPI 259)
This grant writing course is a continuation of EPI 258. By the end of the course, students will complete all remaining grant components, including all research and training sections and ancillary materials. Feedback from instructors and peers will hone the students' applications.
- Grant Writing Workshop on Mentored Career Development Awards Instruction in writing successful grant applications for NIH mentored career development awards. Workshop uses examples from patient-oriented research career development awards (K23s). Underlying concepts for the career development plan, mentoring plan, and research plan also apply to research scientist development awards (K01s) and clinical scientist development awards (K08s).
|Subject Matter-Specific Methods
- Epidemiology of Aging (EPI 210)
Instruction in the issues and methods for the study of the epidemiology of aging with a focus on common chronic diseases in older populations.
- Social Determinants of Health and Health Disparities: What Every Researcher Should Know (EPI 222)
An introduction to the knowledge and skills needed to conduct high-quality research in diverse human populations with an emphasis on understanding the measurement and influence of race/ethnicity and socioeconomic status on health. The first portion of the course is intended for any researcher who intends to work with human subjects, while the second portion is tailored for students with a more focused interest in race and socioeconomic-based health disparities.
- Cancer Epidemiology (EPI 252)
This course will cover the basic understanding of how the principles and methods of epidemiology can be applied to the study of neoplastic diseases.
- Infectious Disease Epidemiology (EPI 253)
Review of intermediate and advanced concepts in infectious disease epidemiology, using examples from the contemporary literature. Topics include social network analysis, vaccine efficacy, epidemic dynamics, evaluation of communicable disease interventions, surveying hard-to-reach populations, prophylaxis and mass drug administration.
- Neglected Tropical Diseases (EPI 261)
An overview of neglected tropical diseases (NTDs), especially those transmitted by vectors (arthropods, snails), their public health importance, and strategies for their control.
- Demographic Methods for Health (EPI 263)
Instruction in basic demographic methods, including population dynamics, fertility, mortality, migration, urbanization, aging, and family structure. The emphasis will be on how and why understanding these factors is important for public health practitioners.
- Spatial Epidemiology (EPI 264)
Introduction to the concepts, principles, and methods for the visualization and analysis of spatially referenced health data. Lectures, discussion and assignments will highlight spatial data analysis techniques with applications in malaria and other infectious and non-infectious diseases prevalent in international settings.