Skip Navigation

Graduate Summer Institute of Epidemiology and Biostatistics

Course Descriptions

One-Week Courses | Two-Week Courses| Three-Week Courses| One-Day Workshops

Three-Week Courses

June 18 - July 6, 2012

Morning 8:30 a.m. - noon

Principles of Epidemiology 340.601.11

Lechaim Naggan
M T W TH F (and Sat June 23)
5 Academic Credits
This is an introductory course in epidemiologic methodology covering study design for investigation of both infectious and chronic diseases. Evaluation of screening programs and health services research will also be discussed. The laboratory problems, based on real data, will include an outbreak investigation, natural history of infectious diseases, validity of clinical tests, survival analysis, and clinical trial and etiologic studies. While there are no formal prerequisites for this course, good quantitative skills and some biologic background are strongly recommended.
June 18-July 6 8:30 a.m. - noon


Two-Week Courses

June 18 - June 29

Morning 8:30 a.m.-noon

Intermediate Epidemiology

Eliseo Guallar
M T W Th F
6 Academic Credits
This course will present and illustrate key methods used in epidemiologic research at an intermediate level. Topics will include causal inference in epidemiology, study designs, measures of disease frequency and association, methods to assess and handle confounding and bias, and analysis and statistical modeling in epidemiologic studies. Prerequisites: Completion of basic courses in biostatistics and epidemiology.
June 18- June 29 8:30 a.m. - noon

Afternoon 1:30 p.m.-5:00 p.m.

Statistical Reasoning in Public Health I 140.611.11
Statistical Reasoning in Public Health II 140.612.11

Natalie Blades and Jessica Myers
M T W Th F
140.611.11 June 18-June 27
140.611.11 June 27-July 6
3 Academic Credits each course
This introductory sequence is intended to provide students with a broad overview of biostatistical methods and concepts used in the public health sciences. The emphasis is on interpretation and concepts rather than calculations or mathematical details. Statistical formulas will be kept to a minimum. An objective is to provide students with an ability to read the scientific literature in order to critically evaluate study designs and methods of data analysis. Basic concepts of statistical inference including hypothesis testing, p-values, and confidence intervals will be introduced. Specific topics will include comparisons of means and proportions, the normal distribution, regression and correlation, confounding, and concepts of study design including randomization, sample size, and power considerations. Additional topics will include logistic regression and an overview of some methods in survival analysis. Examples of the use and abuse of statistical methods will be drawn from the current biomedical literature.
June 18-July 6 1:30 p.m. - 5:00 p.m.


Two-Week Courses| Three-Week Courses| One-Day Workshops

One-Week Courses

June 18 - June 22

Morning 8:30 a.m. - noon

Biostatistical Analysis Of Epidemiologic Data I: Logistic Regression 140.676.11

Steve Selvin
M T W Th F
2 Academic Credits
A case study approach is used to describe and illustrate the issues surrounding intermediate statistical techniques useful in the analysis of epidemiologic and medical data. The course starts with a discussion of the 2 by 2 table, the 2 by k table and combining 2 by 2 tables. Estimation methods (principally maximum likelihood techniques) are included to provide an intuitive background for the following applications. These traditional analyses of tabular data are then contrasted to the application of a linear logistic model approach, which is an important and popular biostatistical tool. Logistic regression methods are then extended to explore the application to continuous data. In the context of regression analysis, key concepts such as independence, confounding and interaction are clearly defined and described. The text for the course is Statistical Tools for Epidemiologic Research (Oxford University Press, 2011) and provides access to a website that contains both STAT and R computer solutions to all example analyses and the data used in the course. Prerequisites: high school algebra and one semester of biostatistics and recommended:two semesters of biostatistics and a course in epidemiology.
June 18- June 22 8:30 a.m. - noon

Comparative Effectiveness Research: Outcome Measurement 340.674.11

Milo Puhan
M T W Th F
2 Academic Credits
Comparative effectiveness research (CER) assesses the effectiveness of competing treatment strategies available in practice and has recently been declared a research priority by the US congress. The proposed course is designed to introduce the students to the measurement, selection and interpretation of outcomes for CER. The course focuses on patient-important outcomes but will also provide introductions to cost ascertainment and analysis as well as to new CER approaches (e.g. network meta-analysis).
June 18-June 22 8:30 a.m. - noon

Genetic Epidemiology in Populations 340. 670.11

Priya Duggal
M T W Th F
2 Academic Credits
This course will cover designs and methods for genetic epidemiology studies of unrelated individuals. Several population genetics concepts relevant to understanding genetic epidemiology designs and statistical tools will be introduced including concepts of quantitative and qualitative traits, genetic risk models, allele/haplotype frequency estimation, and migration/admixture. Methods for the evaluation of single and multiple genetic loci in the context of direct and indirect (linkage disequilbrium) associations with human disease will then be addressed, with examples from both genome-wide and candidate gene approaches. Methods for gene-gene and gene-environment interaction assessment will also be presented. The lecture material will be supplemented with examples using public and simulated data and currently available free software. Prerequisites: Basic knowledge of epidemiology and biostatistics. Enrollment limited; students are required to bring a laptop computer to the class.
June 18- June 22 8:30 a.m.-noon

Topics in Infectious Disease Epidemiology 340.668. 11

Kenrad Nelson
M T W Th FS
3 Academic Credits
This course will provide an introduction to epidemiologic methods used in infectious disease investigations. The importance of surveillance systems in detecting modern epidemics and in the development of effective disease prevention and control strategies will also be presented. An emphasis will be placed on understanding the relationships between the host, the parasite and the environment as they relate to disease causation. The course will explore contemporary epidemiologic methods applicable to old diseases that remain real or potential problems, newly emerging infectious diseases, tropical diseases, and hospital infections. Selected diseases will be discussed to clarify the role of epidemiology in understanding the pathogenesis of infectious processes in individuals and communities. Specific disease examples to be covered include sexually transmitted diseases, tuberculosis, malaria and diarrheal diseases, enteric infections, Legionnaires disease, toxic shock syndrome, acquired immunodeficiency syndrome, and others. This course was previously offered in the Summer Institute as 340.627.11. Prerequisite: Knowledge of basic epidemiology. Please note, the final class for this course meets on Saturday June 23.
June 18- June 23 8:30 a.m.-noon

Nutritional Epidemiology 340.650.11

Laura Caulfield
M T W Th F
2 Academic Credits
The course will provide an introduction to the methodological issues involved in the design, conduct, analysis and interpretation of studies investigating the relationship between nutritional status, diet and disease. Emphasis will be placed on issues such as intraindividual variation, measurement of error, misclassification, correlated variables, population homogeneity, and the use of group versus individual data. The selection and use of dietary and nutritional status assessment methods appropriate for different study designs will be covered, and some experience in their use and interpretation will be provided. The impact of methodological issues, and of the type of study design, on interpretation and conclusions from research in nutrition epidemiology will be emphasized. Prerequisites: None.
June 18- June 22 8:30 a.m.-noon

Conducting Epidemiological Research 340.614.11

Lisa Jacobson
M T W Th F
2 Academic Credits
This course will cover some of the applications of epidemiologic principles in the conduct of observational studies as taught in advanced epidemiologic methods, with specific focus on case-control studies and cohort studies. The focus is on developing skills to conduct and manage a research protocol, monitor the data collection, manage the data, and disseminate results. Covers basic components of a clinical research team, the components of good clinical practice, the responsibilities, expertise and tasks that each member is expected to perform, and organizational, logistical and attitudinal issues that need to be addressed in producing an effective research group. Topics that will be covered include the infrastructure needed for single-site and multi-site studies, selection bias and analytical intent in the determination of populations and methods for recruitment, development of a manual of operations and forms for data collection and administration, data management tools, implementation and review of quality assurance, specimen repository tracking, and useful statistics for evaluating the progress of the study. This applications course is complementary with "Perspectives on Management of Epidemiologic Studies." Prerequisite: intermediate level courses in both epidemiology and biostatistics.
June 18- June 23 8:30 a.m.-noon

Afternoon 1:30 p.m. - 5:00 p.m.

Perspectives on Management of Epidemiologic Studies 340.634.11

Joel Hill
M T W Th F
2 Academic Credits
This is an introductory course dealing with the practical issues of management relating to multi-center cohort studies. Discussion topics include: staffing and training of staff, space and collaboration with GCRC's; recruitment and retention of a prospective, longitudinal cohort, quality control procedures to insure standard data collection within and between field centers. Additionally, there are discussions about leadership, conflict management and team building. Presentation of assigned readings and lectures will be the basis for group discussion. The class will also tackle a problem related to a specific issue from their home environment. There are no prerequisites although some field experience would be helpful. This course is complementary with Conducting Epidemiological Research.
June 18-June22 1:30 p.m.-5:00 p.m.

Data Analysis Workshop I 140.613.11

John McGready
M T W Th F
2 Academic Credits
Intended for students with a broad understanding of biostatistical concepts used in public health sciences who seek to develop additional data analysis skills. Emphasizes concepts and illustration of concepts applying a variety of analytic techniques to public health datasets in a computer laboratory using Stata statistical software. In the first workshop (140.613), students learn basic methods of data organization/management and simple methods for data exploration, data editing, and graphical and tabular displays. Also covered basic statistical methodology including the comparison of means and proportions. Enrollment limited: students must have a laptop computer with Intercooled Stata 11 or Intercooled 12 installed. Student discounts are available for Intercooled Stata.
June 18- June 22 1:30 p.m.-5:00 p.m.
For information on purchasing Stata, please contact Ayesha Khan.

Epidemiology in Evidence Based Policy 340.636.11

Michel A. Ibrahim, Leon Gordis
M T W Th F
2 Academic Credits
This course will focus on how science in general and epidemiology in particular are used to formulate and implement health and regulatory policies. The course will address several questions: How do we distinguish between good science and so called “junk science”? What are the roles of epidemiologists, other professionals—including clinicians, nurses, researchers in other fields—government, industry, and the courts? When should established expert opinions be questioned? What should be done when the available evidence is equivocal and/or controversial? How does science fare in the legislative, regulatory, and judicial settings? What factors and processes are involved after the publication of relevant scientific papers that may support or prevent the development and implementation of appropriate health and public policy? The results of systematic reviews and meta-analyses will be discussed for several case examples such as screening recommendations for breast and prostate cancers, potential hazards of breast implants, tobacco use, general environmental health policies, and issues related to vaccine research and immunization policies. Class time will include lectures, case studies, small group discussions, exercises, and video presentations.
June 18-June 22 1:30 p.m.-5:00p.m.

Ethics Issues in Human Subjects Research in Developing Countries

Nancy Kass, Andrea Ruff
M T W Th F
2 Academic Credits
This course will introduce those enrolled to ethical principles and formal codes of ethics, to key ethical issues that arise in international research. Ultimately, the course will be case-based to enable course participants to work through ethical challenges posed by research conducted in developing countries. Each daily session will be divided between a formal lecture and a case discussion. Case studies will be discussed in small groups and will be based on actual research projects in developing countries, including both clinical and epidemiological/observational research. The course is geared towards U.S. and international faculty, researchers, and students who conduct or fund research in developing country settings and to those who sit on IRBs/research ethics boards. Student evaluation is based on case study exercises and class participation.
June 18-June 22 1:30 p.m.-5:00p.m.

Introduction to Diabetes And Obesity Epidemiology 340.644.11

Cheryl Anderson, Frederick Brancati, Hsin-Chieh Yeh
M T W Th F
2 Academic Credits
Describes the epidemiology and prevention of diabetes, obesity, and associated complications. Discusses methodological issues associated with evaluating these in epidemiologic studies. The course is designed to cover the global epidemics of diabetes and obesity, environmental and genetic risk factors, as well as interventions to improve diabetes outcomes and weight management. The course includes lectures from sever expert faculty members in the Bloomberg School of Public Health and the School of Medicine.
June 18-June 22 1:30 p.m.-5:00p.m.

Survival Analysis 140.606.11

Xiangrong Kong
M T W Th F
2 Academic Credits
Basic concepts and techniques of survival analysis are introduced, including censoring, hazard and survival functions, Kaplan-Meier curves and logrank tests. Parametric inferences are introduced using the exponential and Weibull distributions. Regression analysis of the Cox proportional hazards model, and its extensions to time-dependent covariates, are also be introduced. If time permits, special topics, such as non-proportional hazards models and multivariate survival times, are discussed. An important focus of the course will be using data sets from actual clinical and epidemiological studies to illustrate the introduced statistical methods and show how to make scientific interpretations from the numerical results. SAS and Stata will be the computation softwares used in class. Students can also choose a software based on their own preference when doing exercises. Enrollment limited. Students are required to bring a laptop to class.
June 18-June 22 1:30 p.m.-5:00 p.m.

Epidemiology of HIV/AIDS 340.649.11

Homayoon Farzadegan
M T W Th F
2 Academic Credits
This course will deal with the epidemiology of infection with human immunodeficiency virus (HIV) and AIDS. Current knowledge of the natural history, biology, virology, epidemiology and clinical aspects of AIDS as well as treatment and vaccine clinical trials against HIV will be reviewed. Descriptive, analytic and experimental epidemiologic studies will be critically reviewed to provide a synthesis of our current understanding of the pathogenesis of this infectious disease. No prerequisites. However, an understanding of basic science concepts and biology will be assumed. Basic epidemiological principles and other quantitative skills will prove useful in understanding the distribution of the disease and in interpreting research findings.
June 18-June22 5:00 p.m. - 7:00 p.m. (and two noon-time seminars)


Two-Week Courses| Three-Week Courses| One-Day Workshops

June 25 - June 29

Morning 8:30 a.m. - noon

Biostatistical Analysis Of Epidemiologic Data II: Poisson And Conditional Logistic Regression Analysis 140.677.11

Steve Selvin
M T W Th F
2 Academic Credits
The course presents Poisson regression techniques, which is the primary statistical tool for the evaluation and interpretation of data consisting of counts as well as rates and probabilities. Poisson regression methods are contrasted to the more traditional analyses of mortality and incidence rates. A case/control matched pairs design is examined. A discussion of conditional logistic regression techniques, and bootstrap and randomization estimation methods are presented. The text for the course is Statistical Tools for Epidemiologic Research (Oxford University Press, 2011) and provides access to a website that contains both STAT and R computer solutions to all example analyses and the data used in the course. Prerequisites: high school algebra and one semester of biostatistics and recommended:two semesters of biostatistics and a course in epidemiology.
June 25 - June 29 8:30 a.m.-noon

Epidemiologic Applications of GIS 340.701.11

Carlos Castillo-Salgado
M T W Th F
2 Academic Credits
This introductory course will present the methods and uses of epidemiology towards the development and application of Geographic Information Systems (GIS) in public health. Emphasis is made on the potential of GIS as an epidemiological analysis tool for describing the magnitude of priority health problems, identifying health determinants and supporting health decision making. Specific topics will include epidemiological risk assessment and GIS, thematic mapping of unmet health needs, malaria risk assessment and GIS application for identifying public health problems. The course includes hands-on experience and laboratory exercises using public domain and ESRI software. A required GIS textbook will be available in the online library. Prerequisites: basic knowledge of epidemiology and biostatistics and of use of spreadsheets and tabulations. Students must bring a laptop to class. (2 academic credits)
June 25 - June 29 8:30 a.m.-noon

Pharmacoepidemiology 340.617.11

Sheila Weiss Smith
M T W Th F
2 Academic Credits
Pharmacoepidemiology involves application of epidemiologic methods to study uses and effects of pharmaceutical products in human populations. In addition to the identification and quantification of new adverse events and risk factors, it also includes studies of disease natural history necessary to understand drug effects and studies of drug utilization. This course will cover the development up to and including the seminal Phase 3 clinical trials for approval, the regulatory process, and the use and design of Risk Evaluation and Management (REMS) programs to mitigate known risks; identification of new risks for marketed products, including both active and passive surveillance programs, and the application of data mining; databases and study designs used in pharmacoepidemiology; the decision-making process in pharmacoepidemiology using contemporary examples; and new and emerging developments in the field, including the application of meta-analysis to answer safety questions, the safety gap and pharmacogenomics.
June 25-June 29 8:30 a.m.-noon

Family Based Genetic Epidemiology 340.661.11

Terri Beaty and Rasika Mathias
M T W Th F
2 Academic Credits
This course will present methods commonly used in genetic epidemiology, including statistical methods for measuring familial aggregation, in addition to formal segregation and linkage analysis using family data. The principles and applications of a variety of statistical methods will be presented in detail, and the students will be given the opportunity to implement these methods using both real and simulated data sets as part of the computer lab. Basic understanding of epidemiologic and biostatistical principles is required for this course. Students unfamiliar with genetics should take the "Molecular Biology for Genetic Epidemiology" course. Enrollment limited.
June 25-June 29 8:30 a.m.-noon

Social Epidemiology 340.628.11

Thomas Glass and Manuel Franco
M T W Th F
2 Academic Credits
This one-week course will provide students with a systematic and selective overview of conceptual approaches and research findings related to the impact of social context on the health of populations. Each session will highlight a different area of research on the frontier of this emerging field. Among the social processes to be examined are social inequalities (including social class differences as well as the effects of income inequality per se), social capital and social cohesion, social networks and support, neighborhood characteristics, and race/ethnic differences. Emphasis will be placed on extending the causal chain thought to be associated with patterns of acute and chronic disease to include “upstream” factors related to social context. Includes discussion of methods related to the study of social factors across multiple levels: however this is not intended to be a methods course. The course will be taught as a seminar with limited lecture material. Basic knowledge of epidemiologic and statistical methods (including regression) is required.
June 25-June 29 8:30 a.m.-noon

Clinical Trials: Issues and Controversies 340.635.11

Lawrence J. Appel
M T W Th F
2 Academic Credits
A myriad of complex issues surround the design, analysis and interpretation of clinical trials. This course will cover certain of these common issues and controversies. Topics will include selection of the study population (including issues related to enrollment of minorities and women); choice of "control" and "active" treatments including use of placebos; issues pertaining to informed consent; use of intermediate (or pre-clinical) outcomes versus clinical outcomes; trials in developing countries and premature termination of trials. Examples of published, on-going and planned studies will be used. A visit to a clinical trials research unit will be arranged. Prerequisites: Basic epidemiology.
June 25-June 29 8:30 a.m.-noon

Afternoon 1:30 p.m. - 5:00 p.m.

Data Analysis Workshop II 140.614.11

John McGready
M T W Th F
2 Academic Credits
Intended for students with a broad understanding of biostatistical concepts used in public health sciences who seek to develop additional data analysis skills. Emphasizes concepts and illustration of concepts applying a variety of analytic techniques to public health datasets in a computer laboratory using Stata statistical software. In the second workshop (140.614), students will master advanced methods of data analysis including simple linear regression and correlation, multiple linear regression, and simple and multiple logistic regression. Inclusion of linear splines and interaction terms for both linear and logistic regression modeling will also be covered. Enrollment limited: students must have a laptop computer with Intercooled Stata 11 or Intercooled 12 installed. Student discounts are available for Intercooled Stata.
June 25- June 29 1:30 p.m.-5:00 p.m.
For information on purchasing Stata, please contact Ayesha Khan.

Public Health Dimensions of Global Tuberculosis Control 340.681.11

Jaap Broekmans, Lois Eldred, Jonathan Golub
M T W Th F
2 Academic Credits
Reviews the public health dimensions of global tuberculosis control. It examines the global disease burden and its impact with a special reference to the high-burden countries. Describes the history and current status of the global response, including a critical examination of the DOTS Strategy, the new Stop TB Strategy and the role of newly established global institutions (e.g. Stop TB Partnership, Global Fund to Fight AIDS, Tuberculosis and Malaria, Gates Foundation). Examines the challenges of TB-HIV, MDR- and XDR-TB, and Public Private Mix -DOTS. Research into new tools and interventions will be highlighted. Illustrates national program implementation using concrete examples from the experience in high-burden countries such as Tanzania, Vietnam,Indonesia, and China.
June 25-June 29 1:30 p.m.-5:00 p.m

Non-Inferiority and Equivalence Clinical Trials

Simon Day and Mary Foulkes
M T W Th F
1:30 p.m.–5 p.m.
2 Academic Credits
This course presents the important differences between superiority trials and those intended to show either equivalent effect or to show that one therapy is no worse than another (but might be better). Explores the problems of setting equivalence margins, preservation of some proportion of active control effect, and emphasizes the use of confidence intervals to interpret the results of studies. Discusses special issues of quality of the trial conduct, assay sensitivity, historical evidence of treatment effects and assumptions of constancy of treatment effects over time, including concerns over “bio-creep.” Compares sample size requirements between superiority trials, equivalence trials and non-inferiority trials. Discusses the use of different analysis populations (ITT and per-protocol) and issues of changing conclusions between non-inferiority and superiority. Discusses the regulatory aspects of trial design and interpretation, and reviews existing regulatory guidance.
June 25-June 29 1:30 p.m.-5:00 p.m.

Longitudinal Data Analysis 140.608.11

Michael Griswold
M T W Th F
2 Academic Credits
Covers statistical models for drawing scientific inferences from longitudinal data. Topics include longitudinal study design; exploring longitudinal data; linear and generalized linear regression models for correlated data, including marginal, random effects, and transition models; and handling missing data.
June 25-June 29 1:30 p.m.-5:00p.m.

Methods and Applications of Cohort Studies 340.706.11

Alison Abraham, Alvaro Munoz
M T W Th F
2 Academic Credits
Topics covered in the course include: definition and basic characteristics of cohort studies; recruitment and follow-up procedures; assessment of exposure and outcome; descriptive analysis of cohort data; methods to estimate and compare incidence rates, including Poisson regression; methods for the analysis of disease-free and survival times; estimation and testing of relative hazards (Cox regression) and of relative times; methods to nest case-control and case-cohort designs in cohort studies; procedures to combine prevalent and incident subcohorts; and the role of cohort studies in evaluating interventions and in guiding public policy. Methods will be illustrated using cohort studies in which faculty have been directly involved. Prerequisite: Intermediate-level courses in both epidemiology and biostatistics and some familiarity with data analysis software packages. Students who have successfully completed 340.603 Cohort Studies: Design, Analysis and Applications or 340.728: Advanced Methods in the Design and Analysis of Cohort Studies should not enroll in this course.
June 25-June 29 1:30 p.m.-5:00p.m.

Advanced Issues in the Epidemiology of HIV/AIDS 340.659.11

Homayoon Farzadegan
M T W Th F
2 Academic Credits
Discusses the following topics at an advanced level: (1) Basic science and pathogenesis of HIV/AIDS, (2) Dynamics of the HIV epidemic in five continents, (3) Clinical management of HIV/AIDS in developed and developing countries, (4) Prevention and control modalities against HIV/AIDS, and (5) Future growth of the HIV/AIDS epidemic with special reference to global economic impact of HIV vaccine and eradication issues of HIV/AIDS. Prerequisite: Completion of 340.649.11. Students who have successfully completed 340.844 should not enroll in this course.
June 25-June 29 5:00 p.m. - 7:00 p.m. (and two noon-time seminars)


Two-Week Courses| Three-Week Courses| One-Day Workshops

July 2 - July 6

Morning 8:30 a.m. - noon

Biostatistical Analysis Of Epidemiologic Data III: Semi Parametric Methods 140.678.11)

Steve Selvin
M T W Th F
2 Academic Credits
The topics of rates, tables, misclassification and sample size calculations are presented. The theory and interpretation of rates as a measure of risk are addressed using life tables, non-parametric estimation of survival curves (product-limit estimates) and parametric estimation (exponential model). Analysis of tables with log-linear models is explored as a way to rigorously identify relationships within the summarized data. The topic of misclassification starts with defining the concepts of sensitivity and specificity and then is extended to measures of agreement (for example, Kappa statistics and correlation between categorical variables). Methods to measure the performance and accuracy of criterion based tests are presented (such as a clinical tests for the presence of a disease). Specifically, ROC curves and Bland-Altman analysis are discussed and illustrated with an emphasis on understanding of the application of these techniques to clinical data. The important issues of sample size and controlling the accumulation of errors from multiple statistical tests conclude the course material. The text for the course is Statistical Tools for Epidemiologic Research (Oxford University Press, 2011) and provides access to a website that contains both STAT and R computer solutions to all example analyses and the data used in the course. Prerequisites: high school algebra and one semester of biostatistics and recommended:two semesters of biostatistics and a course in epidemiology.
July 2-July 6 8:30 a.m.-noon

Bayesian Adaptive Trials 340.676.11

Jason Connor
M T W Th F
2 Academic Credits
This course will cover a range of Bayesian adaptive designs and the skills & considerations necessary to construct such designs. The course will begin by reviewing adaptive designs, Bayesian analysis, and Bayesian computation. Each of the next four classes will discuss one or more in a set of real-life Bayesian adaptive designs, considerations that went into each design, and the adaptive decisions that are made in each trial. We consider the operating characteristics of the Bayesian adaptive designs and the benefits and costs of interim analyses, in particular within the regulatory framework.
July 2-July 6 8:30 a.m.-noon

Topics in Clinical Trials Management 340.671.11

Aynur Unalp-Urrida and Roberta Scherer
M T W Th F
2 Academic Credits
Provides an overview of methods related to the day-to-day conduct of multicenter randomized clinical trials with an emphasis on the Coordinating Center perspective. Using case studies of multicenter clinical trials for illustration, emphasizes topics related to Good Clinical Practice, organizational models, applicable Institutional Review Board and the U.S. Food and Drug Administration regulations, methods for randomization and treatment allocation, adverse event reporting, safety and performance monitoring. Encourages discussion of methods, including alternatives to usual practice.
July 2-July 6 8:30 a.m.-noon

Complex Systems And Obesity In Human Populations 340.828.11

Thomas Glass, Manuel Franco, and Takera Igusa
M T W Th F
2 Academic Credits
This course summarizes current knowledge on the epidemiology of obesity across the life course and in different countries. Class will review and critique major explanatory frameworks on the obesity epidemic, including cultural factors, pricing and economic factors, globalization of food production, advertising and media, and environmental determinants. Students will be introduced to systems science as tools for theory building and data analysis with emphasis on application to obesity epidemic. Characterization of the food production and delivery systems. Review potential use of agent based models for evaluation of potential policy solutions to combat obesity.
July 2-July 6 8:30 a.m.-noon

Afternoon 1:30 p.m.- 5:00 p.m.

Molecular Biology for Genetic Epidemiology 340.665.11

Terri Beaty, Alan Scott
M T W Th F
1 Academic Credit
The manipulation and analysis of DNA samples has become fundamental to research including molecular and genetic epidemiology. This course will provides basic knowledge of commonly used recombinant DNA techniques involved in genetic epidemiology and genomics including gene and cDNA isolation, PCR, RFLP analysis, mutational analysis, detection of polymorphisms, SNP analysis, mini and microsattelite detection, and genetic screening.
July 2-July 6 1:30 p.m.-3:00 p.m.

Multilevel Models 140.607.11

Elizabeth Colantuoni
M T W Th F
2 Academic Credits
This course will give an overview of "multilevel statistical models" and their application in public health and biomedical research. Multilevel models are regression models in which the predictor and outcome variables can occur at multiple levels of aggegration: for example, at the personal, family, neighborhood, community and regional levels. They are used to ask questions about the influence of factors at different levels and about their interactions. Multilevel models also account for clustering of outcomes and measurement error in the predictor variables. In this course, we will focus on the main ideas and on examples of multi-level models from public health research. Students will learn to formulate their substantive questions in terms of a multilevel model, to fit multilevel models using Stata during laboratory sessions and to interpret the results. Previous experience with regression analysis is required.
July 2-July 6 1:30 p.m.- 5:00 p.m.

Advanced Data Analysis Workshop 140.620.11

Patrick Tarwater
M T W Th F
2 Academic Credits
Covers methods for the organization, management, exploration, and statistical inference from data derived from multivariable regression models, including linear, logistic, Poisson and Cox regression models. Students apply these concepts to two or three public health data sets in a computer laboratory setting using STATA statistical software. Topics covered include generalized linear models, product-limit (Kaplan-Meier) estimation, Cox proportional hazards model.Enrollment limited; students must have a laptop computer with STATA10 or 11 installed.
July 2-July 6 1:30 p.m.- 5:00 p.m.

Epidemiologic Methods for Planning and Evaluating Health Services 340.638.11

Carlos Castillo-Salgado
M T W Th F
2 Academic Credits
The use of epidemiologic methods in the planning and evaluation of health services is the primary focus of this course. Various epidemiologic techniques and designs will be reviewed as they relate to assessments of health care needs, priority setting, risk assessment, regional health planning, access to care and program evaluation. The format of the course will be a combination of lectures, laboratories and class discussions. The lectures will present topics such as the application of epidemiologic methods in health priority setting, health care needs, evaluation of health interventions and the epidemiologic approach to decision-making. The laboratory sessions and discussions will consider issues in health services research within the practice environments of primary and public health programs. Prerequisite: Completions of basic courses in epidemiology and biostatistics.
July 2-July 6 1:30 p.m.- 5:00 p.m.

Applications of the Case-Control Method 340.605.11

Mara McAdams DeMarco
M T W Th F
2 Academic Credits
Following a review of the basic strengths and problems of the case-control method, the course will examine the application of this most popular method of investigation. Its use will be discussed in evaluation of risk factors, interventions, and as a surveillance tool. The course format will be based on lectures and lab work. Prerequisites: Completion of basic courses in epidemiology and biostatistics.
July 2-July 6 1:30 p.m.-5:00 p.m.

Introduction to the SAS Statistical Package 140.605.11

Aidan McDermott
M T W Th F
2 Academic Credits
Through this course, the student will become an adept user of the SAS statistical package, mastering the skills needed for effective data management, data manipulation, and data analysis. The student will learn how to document work, and make the work replicable. Graphical techniques for displaying data will be discussed. While this course will use the SAS statistical package exclusively, much of the technical knowledge and some of the computing techniques will be applicable to any statistical package. No prerequisites.
July 2-July 6 1:30 p.m.- 5:00 p.m.


One-Week Courses| Two-Week Courses| Three-Week Courses

One Day Workshops

Saturday, June 23

Critical Reading of the Epidemiologic Literature 340.658.11

Moyses Szklo
1 Academic Credit
In this one-day workshop, students will develop skills in critical reading of epidemiological reports. A case-study, problem-based learning approach will be used.Students will read several articles in advance of the course and prepare critiques. During the course, a blend of lectures and discussions will be used.
8:30 a.m.- 5:00 p.m.

Monday, June 25

Draw Your Assumptions Before Your Conclusions: The Use of Causal Diagrams in Epidemiology 140.666.11

Miguel A. Hernan
1 Academic Credit
Causal directed acyclic graphs (DAGs) can be used to summarize, clarify, and communicate one's qualitative assumptions about the causal structure of a problem. The use of causal DAGs is a natural and simple approach to causal inference from observational data. It is also a rigorous approach that leads to mathematical results that are equivalent to those of counterfactual theory. As a result, causal DAGs are increasingly used in epidemiologic research and teaching. The first part of this workshop will provide a non-technical overview of causal DAGs theory, its relation to counterfactual theory, and its applications to causal inference. It will describe how causal DAGs can be used to propose a systematic classification of biases in observational and randomized studies.
The second part of this workshop will present practical applications of causal DAGs theory to examples taken from various research areas in epidemiology, including cancer, pregnancy outcomes, and HIV/AIDS. It will also describe the bias induced by the use of conventional statistical methods for the analysis of longitudinal studies with time-varying exposures.

Saturday, June 30

Methods for Clinical and Translational Research 340.725.11

Jonathan Samet
1 Academic Credit
This course provides an overview of the methods of translational research. Emphasizes developing skills in the interpretation and application of findings of translational research. Topics include study design, biomarkers, statistical analyses, validation strategies, and evidence synthesis methods.
8:30 a.m.- 5:00 p.m