Course Descriptions & Syllabi
Clinical & Translational Research Program
|Course Title/Description||Course Number||Credit Hours|
|Advanced Biostatistics (PDF)|
The role of regression in all its diversity in data analysis. This is purely an applied class with examples culled from a variety of sources. The software R will be used for all computational needs.
|Biostatistics in Research (PDF)|
Seminars or tutorial sessions dealing with special topics in biostatistics related to research and application basic to field of environmental health.
|Clinical Research Scholars Seminar (PDF)|
This seminar will cover topics not typically covered in most courses, such as how to write papers, how to find funding, how to present research, and how to negotiate for jobs. The seminar will allow students from all clinical and translational research tracks to see and critique each others' research-in-progress presentations and enable students to meet with various cutting-edge clinical researchers. It will foster further interaction among other students in the Clinical & Translational Research Training program.
|Collaboration & Team Science (PDF)|
This course provides an overview of the Science of Team Science (SciTS) for investigators who are (or will be) engaged in translational research and will be working in teams. In addition to examining the theoretical and research literature on the dynamics of small groups, the course will include an examination of the construction and maintenance of high functioning teams. Tools and exercises for assessing and improving team skills will provide hands-on experiences for learners. Each class session will be divided into two parts: 1) an exploration of a particular topic related to teams, team functioning, and team science, and 2) a discussion of one or more cases in which class members function as a consulting team in order to assess the case scenario and to develop recommendations for corrective action.
|Comparative Effectiveness & Patient-Centered Outcomes Research (PDF)|
This course will allow students to recognize the strengths and limitations of common study designs for conducting comparative effectiveness research (CER), acquire knowledge and skills of the different statistical methodologies common in CER, learn qualitative study designs that can be applied to studies in CER and patient-centered outcomes research (PCOR), and more.
|Communicating Your Science (PDF)|
Graduate students in science related fields receive training in cutting-edge research, but rarely on how to explain their research to non-specialists. Communicating Your Science will enable students in scientific disciplines to develop the skills needed to explain their research to non-specialists and public audiences. Class sessions will address a variety of communication areas, including speaking and writing to lay audiences, reporting research results to community members, preparing briefings for policy-makers, and communicating with different media outlets. Students will be exposed to a broad array of professional academic researchers and community members relating to the various course topics and discussions.
|Computational Statistics (PDF)|
Using R and SAS software in basic PROC procedures, simulations, and advanced statistical methods.
|Data Analysis with R & SAS (PDF)|
This course exemplifies the role of the computing software R and SAS in data analyses. The course will cover the basics of R, (including data structures; data manipulation; loops and functions; graphics; statistical tests; and sample size calculation), and SAS, (including importing data and different procedures).
|Decision Analysis & Cost-Effectiveness Analysis (PDF)|
This course will introduce participants to the methods and applications of decision analysis, cost-effectiveness analysis, and cost-benefit analysis in medical decision making. Topics will include Bayes’ theorem and evaluation of diagnostic tests, the design and interpretation of decision trees, sensitivity analysis, Markov models, utility assessment, and economic analysis of healthcare programs. Examples will be drawn from both the individual patient and health policy perspectives. Students will learn how to use decision analysis software.
|Design & Management of Field Studies (PDF)|
Opportunity to acquire knowledge and skills in many aspects of the designs and conduct of field based research. Includes writing a hypothesis and writing a research proposal or grant application, designing questionnaires, survey sampling, sample size determination and the art of presenting results and evaluating research.
|Epidemiology & Biostatistics Division Seminar (PDF)|
This weekly seminar features faculty from the Division of Epidemiology and Biostatistics, advanced students, epidemiologists, biostatisticians, and other persons from public and private institutions. The seminar offers a forum to learn about ongoing faculty research and provides an opportunity for students working on their thesis or dissertation to gain experience in presenting findings and fielding questions from the audience. Nuts and bolts of research that are often not available in textbooks are discussed.
|Epidemiology of Cancer (PDF)|
A general overview of known associations of environmental and occupational factors with various types of cancer; includes discussion of types of studies that give rise to associations and causation.
|Epidemiology of Infectious Diseases (PDF)|
The course covers the epidemiologic, serologic, and public health aspects of modern infectious diseases, their transmission, and methods of control.
|Experimental Design (PDF)|
This course covers the statistical basis for experimental designs and the analysis of experimental data. Designs that are discussed include the two-group independent and correlated design; completely randomized factorial design for more than 2 groups; nested and split plot models; repeat measure designs; complete and incomplete block designs and fractional factorial designs. Associated topics include tests for homogeneity of variance; power analysis; methods for performing multiple comparisons; fixed, random and mixed models; construction of an EMS table; and construction of proper (direct and pseudo-) F-ratios.
|Introduction to Biostatistics (PDF)|
The course covers descriptive statistics, probability distributions, estimation, types of error, significance level, hypothesis tests, sample size, correlation, linear regression, non-parametric methods.
|Introduction to Epidemiology (PDF)
This course will introduce you to the foundational concepts of epidemiology. We will examine study design types and how to choose the appropriate one using real world examples. You will learn the equations used for calculating risk as well as how to control for bias and confounding. We will also explore public health policy and the common ethical issues encountered in epidemiologic studies. Additionally, the project gives you the opportunity to critically examine and analyze a study on a topic that interests you.
|Introduction to Medical Informatics (PDF)|
This course will cover medical informatics and its relation to patient care, data extraction, databases, and clinical research. Evidence-based medicine and clinical effectiveness research will be highlighted in the discussions. Strengths and limitations of hardware, systems, and data will be discussed. Specific topics will include: common terms; security and confidentiality; general hardware information; general network architecture information; standards and identifiers; data entry methods; interfaces and data integrity; computer-based medical information systems; medical imaging systems; databases, data marts, and data warehouses; data mining and reporting; expert systems; the Internet and Intranet and healthcare; education and training technologies; the product evaluation process; vendor relationships; general financial information; and personal productivity applications. Learning objectives will be achieved using a variety of methods including: didactic lectures, demonstrations, self-study, and student projects.
|IRB Process & Protocol (PDF)|
This course gives students hands-on experience with preparing a human subject research study and submitting it to the Internal Review Board (IRB).
Meta-Analysis is the systematic quantitative review of all research studies directed toward a particular scientific or policy question. This course will cover all aspects of this process, including searching and evaluating research reports, extracting data, computing measures of effect size for continuous and categorical data, estimation of statistical models using SAS and WinBUGS software, and preparation of a manuscript. Students will conduct a meta-analysis on a topic of their choice, subject to instructor approval.
|Molecular Epidemiology (PDF)|
The course covers how biomarkers can be used in epidemiologic research; scientific, technical and ethical issues in the use of biomarkers and a range of applications for the use of biomarkers in the study of various diseases.
|Perinatal & Pediatric Epidemiology (PDF)|
Perinatal and Pediatric Epidemiology (PPE) is a branch of epidemiology studying the risk factors that may affect human reproduction, pregnancy, birth outcomes, fetal and child development, and maternal and child health conditions. PPE utilizes surveillance, case-control study, cohort study, clinical trial, and community prevention trial to provide data regarding infertility, pregnancy loss, stillbirth, pregnancy complications, adverse birth outcomes, infant and child disorders to guide prevention efforts. The PPE course will provide an introduction to perinatal and pediatric health outcomes from a population viewpoint, describe major risk factors identified, summarize research progress and limitations, and stimulate students to identify unsolved questions and design new studies in the relevant areas.
|Phase I/II Clinical Trials Research & Design (PDF)|
Regulatory, statistical and operational issues in phase I trials will be discussed. The use of first dose in humans, dose escalation schemes, determination of maximal tolerated dose, mass balance, metabolism and bioavailability will be covered along with drug-drug interaction and food-effect.
|Quality Improvement & Patient Safety (PDF)|
This course will cover the fundamentals of quality improvement and patient safety. It will use a framework of human factors to facilitate understanding complex system failures and successful strategies to reduce hazard in industrial and medical environments. The concepts are taught using a case-based format to explore common human and organizational sources of failure, such as missing or inert knowledge, communication/collaboration, clumsy technology, human computer interaction (alerts and reminders), and role of a safety culture. The second half of the course is devoted to learning approaches for implementing evidenced-based practices based on Rogers’ theory, where adopting innovation in an organization is divided into two major activities: initiation and implementation.
|Regression Analysis (PDF)|
The course covers the following topics: linear regression, least squares, multiple regression models, model diagnostics & building, correlation analysis, introductory analysis of variance and introductory logistic & Poisson regression models.
|Research Methods for Human Population Studies (PDF)|
This course provides the student with an understanding of the methods for undertaking health research conducted in human populations. The course is structured around the selection and appropriate implementation of methods of sampling, participant recruitment and retention, data collection (such as questionnaires and interviews), measurements, biospecimen procurement and initial processing, and information dissemination.
|Scientific Integrity (PDF)|
This course provides an overview of the ethical norms and regulatory issues that serve as the foundation of the responsible conduct of research (RCR).
|Statistical Genetics (PDF)|
Course objectives are to learn how various genetic data are generated and analyzed and to understand the linkage hybridization between statistical genetics and molecular, genetic, and cancer epidemiology. Didactic lectures include application of statistical procedures in conducting population genetic analyses for localization of disease-susceptibility genes and estimation of genetic risks, including gene frequency estimation, detection and estimation of the extent of population substructure effects, measurement and estimation of genetic admixture proportions and the nature of discrete genetic data, application of the Hardy-Weinberg law, model-free measures of association, the likelihood method, and principles of genetic inference and segregation analysis.
|Statistical Computation & Software (PDF)|
This course is designed to provide some basic knowledge and skills in statistical computation using three different software packages: SAS, SPSS and R. For SAS, the class will offer computation using both SAS Program and SAS Enterprise. Many times students find instructors using different statistical software in their classes, especially their statistic and epidemiologic classes. It becomes challenging for students to take these courses and learn the software packages at the same time. In this class, students will learn how to use different software/solve the same problem from the same dataset. That way they will have a better sense on how these software packages are connected, and will be more confident in computation when they take additional statistic and epidemiologic classes.
|Study Design & Analysis (PDF)|
This course builds upon the epidemiologic concepts covered in the Introduction to Epidemiology course. Clinical epidemiologic study designs are examined in more detail and variants of the basic designs are introduced. Nested case-control designs, clinical trials, matching, and innovations such as case-cohort and counter-matched designs are examined in depth. Biostatistical methods appropriate for each type of study design are described and quantitative examples provided. Two special computer lab sessions are included to give students hands-on experience using SAS to analyze clinical epidemiologic data.
|Scientific Writing (PDF)|
Students will learn to communicate the findings of their research and investigations more effectively, and expedite publication of their manuscripts.
|Survey of Clinical & Translational Research (PDF)|
A general overview of a variety of topics in clinical research including interpreting regression and survival analysis, developing a successful relationship with a mentor, and project management.