Experienced statisticians, epidemiologists and clinical faculty teach these seminars free of charge. Each seminar and workshop is tailored to the needs and level of its audience. Instructors often encouarge active participation, which can lead to lively discussions. Class content makes use of current professional literature for your medical specialty.
Click any of the following categories for descriptions of relevant seminars and workshops.
Statistics
Grant Development& Study Design
Database and Software Workshops
Which statistical test should I use?
This seminar introduces beginning researchers to the most common types of basic statistical tests. Topics covered include t-tests and ANOVA, as well as their non-parametric equivalents. The chi-square test is also covered. The seminar concludes with several clinical examples where participants choose the correct statistical test. Learning Objectives: By the end of this seminar, participants will be able to describe basic statistical tests and know when to use them.
Pitfalls in statistical analysis
This seminar introduces participants to the top list of the most common mistakes all levels of researchers make when analyzing data, and how to avoid making them. Topics include multiple testing, matching your analysis to your study design and confounding. Interaction from the audience is encouraged, and participants present examples of the mistakes they have seen in the literature. Learning Objectives: By the end of this seminar, participants will become more aware of issues in the design and analysis of their research projects.
Evaluating medical journals from a statistical perspective
This interactive journal club focuses on journal articles from your field. Since the comprehensive discussion relies on student input about appropriateness of study design, discussion questions such as the following are sent out ahead of time: Do the aims and analyses match the stated hypotheses? Have power calculations been performed? Do the statistical analyses, tables, and graphs seem appropriate? Are limitations mentioned? Learning Objectives: By the end of this seminar, participants will be better prepared to critically evaluate published literature.
Linear and Logistic Regression
This seminar introduces participants to linear and logistic regression, the most common types of regression. Discussion topics include how to choose when regression should be used, and how to decide if linear or logistic regression is most appropriate. Topics covered include basic assumptions, modeling strategies, and how to interpret the results of regression models. Learning Objectives: By the end of this seminar, participants will be prepared to delineate the advantages of regression models, know whether to use linear or logistic regression, and be able to interpret the results.
Modeling Time-to-Event Outcomes
This seminar introduces participants to “Survival analysis,” including Kaplan-Meier curves and Cox regression, both of which handle time-to-event data. Topics covered include how time-to-event data are different from most other types of data and why special techniques are needed to handle them. Participants receive a “behind-the-scenes” view of how survival estimates are calculated, and interpretations of Kaplan-Meier curves and Cox regression output are discussed. Learning Objectives: By the end of this seminar, participants will be better equipped to correctly interpret survival analysis results presented in the medical literature.
Statistical Principles of Meta-Analysis
This seminar is an overview of the principles of meta-analysis as applied to randomized controlled trials and observational studies. Content includes the basic conceptual framework of analysis, examples of implementation, different approaches in the field, and current work. Topics covered include principles of combining data, caveats to be aware of, available metrics and methods for combining data, and heterogeneity (assessing for it, accounting for it, and explaining it). Learning Objectives: By the end of this seminar, participants will be better equipped to collaborate with systematic review experts in designing and performing meta-analyses in their area of research interest.
How many subjects do I need for my study?
This seminar will help you answer that question. We start with a review of hypothesis testing and why sample size calculations are important, and then move on to the basics of doing a sample size calculation. Potential complications introduced by different study designs are also discussed. Finally, there is an overview of helpful statistical packages and online sources for running sample size calculations. Learning Objectives: By the end of this seminar, participants will be able to do simple power calculations and identify characteristics of more complex sample size calculations that require a statistician.
Introduction to Design and Analysis of Clinical Trials
This seminar will review the difference between observational and experimental studies; randomization and why it limits confounding bias; randomization schemes; inclusion/exclusion criteria; placebo controls; blinding; clinical trial designs (basic designs, cross-over studies, factorial designs, delayed start, equivalency studies); compliance/adherence; issues in analysis (interim analyses/DSMB responsibilities, intent-to-treat vs. per protocol/as-treated analysis, univariate vs. multivariate adjustment, subgroup analysis); and threats to RCT internal and external validity. Learning Objectives: By the end of this seminar, participants will be more adept at evaluating published clinical trials and will have gained a deeper understanding of the methodologies underlying their own experimental research.
Designing Clinical Research
This seminar provides an overview of various research designs, including their strengths and weaknesses, and their common applications, and criteria for causal inference. Learning Objectives: By the end of this seminar, participants will be able to define basic biometric tools used in epidemiology such as measures of disease frequency and measures of associations between a given risk factor and disease, identify major sources of bias in epidemiologic research (including selection bias, measurement error, and confounding), and describe how such biases can be evaluated and reduced.
Why studies fail: bias and confounding
This seminar introduces participants to the spurious associations in clinical research that can arise due to various systematic biases, including selection bias, confounding, and information bias. Each type of bias is discussed, as well as ways in which they can be prevented or mitigated in the design and analysis of observational research studies. Learning Objectives: By the end of this seminar, participants will be able to anticipate how bias may distort measures of effect in their research, and be more aware of how to reduce its impact.
Screening Tests
This interactive seminar offers a look at the goals of screening tests, what characteristics make a disease ideal for screening, and the attributes of a good screening test. Participants are introduced to quantitative measures of screening test validity and have the opportunity to discuss potential common biases of screening test evaluations and how to evaluate whether or not a screening program is effective. Current controversies in prostate and lung cancer screening are used to illustrate concepts, and participants are encouraged to bring their own screening-related questions. Learning Objectives: By the end of this seminar, participants will be better prepared to evaluate the potential benefits and risks of screening tests and epidemiologic studies of their efficacy.
Writing a Research Grant
This presentation provides an overview of the basic elements of preparing and submitting a grant application, using examples from funded NIH grant applications. The presenter describes the organization and content for each section of the grant for both observational and interventional studies, gives tips on grantsmanship and improving readability, and points to online grant-writing resources. An interactive segment will focus on formulating the outline of a protocol for participants’ study questions. Learning Objectives: By the end of this workshop, participants will be better equipped to prepare a strong grant application.
Designing a Study and Developing a Protocol
This interactive workshop presents the key steps in study design and implementation, including how to formulate a study question, which study design to choose, what to consider when developing a protocol, how to deal with logistical issues in protocol implementation, and how to design an ethical study. The workshop is structured as a short didactic session followed by a small group interactive session where participants go through the steps of formulating a study question and choosing a study design. Learning Objectives: By the end of this workshop, participants will be able to describe the many steps involved in undertaking a clinical trial to answer a research question.
Observational study designs
This session will review the major observational epidemiologic study designs, including cross-sectional surveys, retrospective and prospective cohorts, and case-control studies. The major selection strategies, design elements, measures of association, and strengths and limitations will be presented, along with examples from publications pertinent to the research interests of the audience. Learning Objectives: By the end of this seminar, participants will be more adept at matching a particular study design to a given research question and setting.
Aiming for Success! A Writing Workshop for Researchers
This seven-session workshop focuses on the most important area of grant proposals, the Specific Aims section, exploring ways to attract reviewers to the significance, innovation, and approach of a study, right from that very first page. Some questions the workshop addresses: How do I come up with a compelling central idea for my writing and how do I stay on point? How can I be a better collaborator, offering and being able to receive and use feedback effectively? The primary text for the class will be the participants’ own Specific Aims pages, which we will revise together. Learning Objectives: By the end of this workshop, participants will have a Specific Aims section that excites and inspires, leading to a proposal that will do the same. They will also be prepared for and comfortable with the new formats for NIH grant proposals.
Building a Database From the Bottom Up
This workshop introduces participants to database design and concepts. Topics covered include variable naming and coding, flat vs. relational databases, and basic data-cleaning tips. Students will have an opportunity to put in practice what they have learned by creating the variable names and coding for a real case-report form and to set up the database in Excel. Learning Objectives: By the end of this workshop, participants will be able to create a simple database in a format that can be read by statistical software.
Using Macros and ODS in SAS
In this workshop, students work at their own computers to learn about SAS macros and ODS (output delivery system). Macros allow the programmer to perform the same task on many variables without having to write a separate procedure for each one, and ODS allows the programmer to print output from a procedure to a file for later use in a data step. Combining ODS with macros allows the programmer to create customized professional tables. Learning Objectives: By the end of this workshop, students will be able to use ODS and macros to create a typical Table 1 for a journal article.
Using JMP 8 Software
This workshop introduces participants to JMP 8 software as a statistical tool in exploring their research data. Activities include calculating sample size and power, entering and managing data in JMP, conducting basic statistical tests and interpreting the output, and creating and exploring descriptive graphs and plots of the data. JMP 8 is a menu-driven interface similar to Excel, produced by SAS, with numerous options for exploring research data. Prerequisite: Participants should be familiar with basic statistical testing and regression models and their interpretation. Learning Objectives: By the end of this workshop, students will be able to apply their knowledge of basic statistical analysis and explore their research data using this software program.
Incorporating Spatial Data in Studies
This hands-on workshop introduces researchers to ways of incorporating spatial data into clinical studies. Whether you are interested in using publicly available data sources or collecting your own, this workshop provides an overview of the common statistical tools for spatial data analysis. Examples are presented from research in modeling disease clustering, environmental hazards, and access to health services. Learning Objectives: By the end of this workshop, participants learn the difference between point-referenced, point-pattern, and areal data and tools for analyzing each. Learning Objectives: By the end of this workshop, participants will be familiar with the fundamentals of spatial data analysis.
Summarizing Data Using Excel
Participants will learn to use Excel functions and Excel’s AnalysisToolPak Excel to describe their data. Participants are encouraged to bring laptops to analyze the presented datasets during the seminar. Learning Objectives: By the end of this workshop, participants will be able to use Excel to summarize data both in tabular and graphical form.
Analyzing Data Using Excel
This seminar will show participants how to use MS Excel to test for statistically significant associations in data. Basic statistical approaches including confidence intervals, hypothesis testing, and p-values will be presented and their use and interpretation demonstrated on clinical datasets. Participants are encouraged to bring laptops to analyze the presented datasets during the seminar. Learning Objectives: By the end of this seminar, participants will be able to run basic statistical tests in Excel and understand the output.
