SER is pleased to offer the following 2025 Workshops! Some workshops are being offered virtually, some in person, and a few workshops are being offered in both formats. Review the date and time details below for specifics on each workshop.
Morning Workshops
Workshop Details
In Person:
June 10, 2025
8:30am – 12:30pm
Target Audience: Intermediate
Quasi-Experiments in Epidemiology: Staggered Adoption Difference-in-Differences and Synthetic Control Methods
Presenters
Lee Kennedy-Shaffer, Department of Biostatistics, Yale School of Public Health
Description
In recent years, quasi-experimental analyses have become particularly important in epidemiologic research, especially on health policy questions. New methods for these analyses have also arisen, especially in the quantitative social sciences literature, and biases and statistical challenges pointed out in previous methods.
This workshop will introduce participants to Read more
Workshop Details
In Person:
June 10, 2025
8:30am – 12:30pm
Target Audience: Intermediate
ABC's of Estimating Equations
Presenters
Paul Zivich, UNC Chapel Hill
Rachel Ross, Columbia University
Bonnie Shook-Sa, UNC Chapel Hill
Description
Estimating equations are a powerful tool set for epidemiologists, with many familiar estimators being special cases. Importantly for epidemiologic research, estimating equations allow for the simultaneous estimation of multiple parameters and a streamlined approach to estimate variances of parameters that depend on other parameter estimates. Read more
Workshop Details
In Person:
June 10, 2025
8:30am – 12:30pm
Target Audience: Intermediate
Modern Causal Mediation Analysis
Presenters
Ivan Diaz, NYU
Nima Hejazi, Harvard University
Nicholas Williams, Columbia University
Description
Causal mediation analysis can provide a mechanistic understanding of how an exposure impacts an outcome. However, rapid methodologic developments and few formal courses present challenges to implementation. Beginning with an overview of classical direct and indirect effects, this workshop will present recent advances that overcome limitations of previous methods, allowing for: (i) continuous exposures, (ii) multiple, non-independent mediators, and (iii) effects identifiable in the presence of intermediate confounders affected by exposure. Read more
Workshop Details
In Person:
June 10, 2025
8:30am – 12:30pm
Target Audience: Beginner
Using Community-Engaged Research Approaches to Advance Equity and Inclusion
Presenters
Rachel Bergmans, University of Michigan
Description
There is recognition that diversity, equity, and inclusion should be prioritized in research, and that anti-oppression research is needed to address inequities. Community-engaged approaches offer a model for achieving these goals. However, few researchers are well equipped to implement community-engaged approaches and do not know where to start. The overarching goal of this workshop is to provide participants with tools and strategies that they can begin to implement. Content for this workshop is rooted in community-engaged research principals, including reflection on social identity and intersectionality. This interactive workshop combines a mix of didactic presentation, examples, activities, and discussion. Learning objectives: Read more
Workshop Details
In Person:
June 10, 2025
8:30am – 12:30pm
Target Audience: Beginner
Yes you can!...Write a successful K proposal
Presenters
Kaitlyn Stanhope, Emory University
Christine Gray, Duke University
Description
Writing a K-series NIH proposal is exciting but daunting. We will go over what a K is (and is not), and walk through the entire process, from generating feasible and fundable ideas to navigating the grant submission process. We will distinguish different K mechanisms, focusing on the K01 and K99-R00, and tradeoffs between them. Topics will include aligning aims with training goals, strategies for constructing a mentoring team, budget considerations (including effort and subawards), and how a K fits into a research-oriented career trajectory. We will review the expected format and structure of K proposals, and offer tips on grantsmanship and writing reviewer-friendly proposals. We will cover terminology, as well as the NIH review process and scoring.Read more
Workshop Details
In Person:
June 10, 2025
8:30am – 12:30pm
Target Audience: Beginner
Epidemiological analysis of electronic health records
Presenters Description
Neal Goldstein, Drexel University
Milena Gianfrancesco, Pfizer, Inc
Increasingly data mined from the electronic health record (EHR) are being used for secondary analysis in epidemiological research. But more data does not equate to better quality research. In this workshop, we will cover the fundamentals of working with EHR data and designing and conducting valid epidemiological analyses. The workshop will be half didactic lecture and half interactive group exercise. Participants will work with real EHR data as the basis of the group exercises, and therefore will be required to complete a small pre-workshop training to obtain access to these data. Following the group exercise, all participants will reconvene to discuss the challenges and opportunities of working with real EHR data. Read more
Workshop Details
In Person:
June 10, 2025
8:30am – 12:30pm
Target Audience: Beginner
"Peerspectives" on peer review at major biomedical journals: A crash course for early-career researchers
Presenters Description
Toivo Glatz, Charite- Universitatzmedizin Berlin
Timothy Feeney, The BMJ
Jessica Rohmann, Charite-Universitatsmedizin Berlin
What do top biomedical journal editors look for in submitted articles? How can we ensure high-quality methods and reliable results in the published literature that inform guidelines and clinical decision-making? Join us for a 4-hour workshop that will explore these questions and more! We have specially crafted this session for students and researchers with little or no prior peer review experience. Read more
Afternoon Workshops
Workshop Details
In Person:
June 10, 2025
1:00pm – 5:00pm
Target Audience: Intermediate
Causal inference for time-varying (longitudinal) exposures
Presenters
Lina Montoya, UNC Chapel Hill
Laura Balzer, UC Berkely
Description
This workshop applies the Causal Roadmap to estimate causal effects with multiple intervention variables, such as the cumulative effect of an exposure over time and the effects on survival-type outcomes with right-censoring. We will cover longitudinal causal models, identification in the presence of time-dependent confounding, and estimation of joint treatment effects using G-computation, inverse probability weighting (IPW), and targeted minimum loss-based estimation (TMLE) with Super Learner. During the workshop session, participants will work through the Roadmap using an applied example and implement these estimators with the ltmle R package. Prior training in causal inference with a single time-point exposure is highly recommended.
Workshop Details
In Person:
June 10, 2025
1:00pm – 5:00pm
Target Audience: Intermediate
Beyond the Average Treatment Effect -- Estimating effects of complex exposures
Presenters
Ivan Diaz, NYU
Nicholas Williams, Columbia University
Kara Rudolph, Columbia University
Description
We tend to be most familiar with estimating the effects of binary treatments or exposures. The classic average treatment effect (ATE), risk difference, risk ratio, and odds ratio are all examples of this. However, the exposure may be more complicated than a simple binary variable. For example, there may be multiple exposures or multiple components of an exposure, and it is most relevant to consider intervening on them jointly. In addition, sometimes exposures are continuous, and one would like to have an easy-to-interpret causal effect. In this workshop, we will walk through how to define causal effects (what are called causal estimands) for categorical, continuous, and multiple exposures. Read more
Workshop Details
In Person:
June 10, 2025
1:00pm – 5:00pm
Target Audience: Beginner
Git and GitHub for Public Health Research
Presenters
Lauren Wilner, University of Washington
Corinne Riddell, University of California, Berkeley
Description
Version control, the practice of tracking and managing changes to statistical code, is essential for reducing errors in a statistical analysis. However, many epidemiologists are not trained to do this and are unsure how it fits with institutional review board (IRB) protocols and privacy standards. In this workshop, we will provide an introduction to git and GitHub, to equip epidemiologists with version control tools that also meet ethical standards. Read more
Workshop Details
In Person:
June 10, 2025
1:00pm – 5:00pm
Target Audience: Beginner
A Primer on Quantile Regression for Epidemiologists
Presenters
Anusha Vable, UC San Francisco
Description
Quantile regression is a powerful method of evaluating how an exposure affects the entire outcome distribution; this is distinct from analyses on how exposures impact the mean of an outcome, which are more common in the epidemiological literature. However, quantile regression remains underused in epidemiology. Our proposed workshop has two aims: 1) introduce participants to quantile regressions with a focus on distinguishing between estimators targeted at the conditional versus marginal outcome distribution; and 2) equip participants to conduct quantile regression analyses in statistical packages like R or Stata. Our workshop will have three phases. Read more
Workshop Details
In Person:
June 10, 2025
1:00pm – 5:00pm
Target Audience: Beginner
Introduction to Monte Carlo Simulation
Presenters
Ashley Naimi, Emory University
Description
This course will focus on the design and analysis of Monte Carlo simulation studies. Simulation studies are an invaluable tool in any analyst’s kit. They can facilitate developing a firm understanding of basic and advanced methods concepts, and provide a flexible means of evaluating whether analytical techniques will work as expected under specific conditions. Read more
Workshop Details
In Person:
June 10, 2025
1:00pm – 5:00pm
Target Audience: Intermediate
Bayes in Boston: Bayesian Methods for Epidemiologists
Presenters
Kevin T. Chen, University of California, Berkeley, School of Public Health
Catherine Li, University of North Carolina at Chapel Hill
Patrick T. Bradshaw, University of California, Berkeley, School of Public Health
Description
Bayesian statistical inference involves updating prior knowledge with observed data. This paradigm enables incorporation of external information into an analysis, and acknowledgement of multiple sources of uncertainty, thereby facilitating diverse sensitivity analyses including those that account for unobserved variables, measurement error, and selection bias. Additionally, Bayesian methods allow for estimation of various target parameters, which make them particularly useful for causal inference. Despite their utility, epidemiologists have few opportunities for formal training in Bayesian methods. We will cover the fundamentals of Bayesian regression and demonstrate applications of Bayesian approaches to bias analysis and causal inference. Read more
Workshop Details
In Person:
June 10, 2025
1:00pm – 5:00pm
Target Audience: Intermediate
Practical coding to address the reproducibility crisis
Presenters
Scott Zimmerman, University of California San Francisco
Erin Ferguson, University of California San Francisco
Description
While replication of results is an essential component of the scientific method, recent work has shown that many findings can not be reproduced. In this context, approaches allowing for rigorous evaluation of how analytic decisions affect estimates are needed. Proposed approaches (e.g. multiverse analyses, multidimensional sensitivity analyses, and simulations sampling from a parameter space) require specifying and iterating over hundreds or thousands of analysis options, models, or datasets. However, little guidance has been provided for how to write and organize code to efficiently iterate over large numbers of specifications. Read more
Workshop Details
In Person:
June 10, 2025
1:00pm – 5:00pm
Target Audience: Intermediate
Single World Intervention Graphs (SWIGs) for the practicing epidemiologist
Presenters
Aaron Sarvet, University of Massachusetts
James Robins, Harvard University
Mats Stensrud, École polytechnique fédérale de Lausanne
Kerollos Wanis, MD Anderson Cancer Center
Description
The use of directed acyclic graphs (DAGs) has become routine in epidemiology. However, DAGS offer limited convenience in many common settings, including those involving sustained strategies, contra-indications to treatment, competing events, and censoring, to name a few.
In this session we introduce a relatively novel innovation, termed the Single World Intervention Graph (or SWIG). SWIGs are closely related to DAGs, with the primary distinction that they are constructed uniquely for the specific causal question at hand. SWIGs are the graphical tools most closely aligned with the Target Trial framework, and thus are gaining increasing attention in epidemiology. When an investigator has articulated a causal question in the form of a Target Trial, the corresponding SWIG is easily derived from a DAG using simple rules. Classical assumptions for inference on a broad set of causal questions can then be read directly off the SWIG using familiar graphical criteria. Read more
Workshop Details
In Person:
June 10, 2025
1:00pm – 5:00pm
Target Audience: Intermediate
Modern use of propensity scores: weighting, estimands, and moving beyond the bootstrap for variance estimation.
Presenters
Tobias Kurth, Charité – Universitätsmedizin Berlin
Timothy Feeney, University of North Carolina Chapel Hill
Description
Propensity scores, defined as the probability of treatment conditional on covariates, have gained widespread use in biomedical and public health research. Propensity scores are intuitively appealing, and estimation using standard software packages is straightforward. Two common approaches using propensity scores, matching and weighting, allow researchers to target various causal estimands such as the average treatment effect (ATE), the average treatment effect in the treated (ATT), and the average treatment effect in the untreated (ATU). Proper estimation of these estimands requires careful attention to causal identification conditions, and obtaining consistent estimates of the standard error can be computationally intensive. Read more
Evening Workshops
Workshop Details
In Person:
June 10, 2025
5:30pm – 7:30pm
Target Audience: Beginner
An introduction to directed acyclic graphs: What you never wanted but needed to know about bias and didn't even know to ask
Presenters
Ian Shrier, McGill University
Description
This workshop will introduce participants to directed acyclic graphs (DAGs). We will review the basic principles and
show how they can be used to determine appropriate sets of variables for estimating total causal effects of
exposure (treatment). Participants will work through concrete examples of increasing complexity. We will also
introduce how DAGs can be used in more advanced applications, including natural and controlled direct and
indirect effects and study design.
Workshop Details
In Person:
June 10, 2025
5:30pm – 7:30pm
Target Audience: Intermediate
Writing a cohesive and compelling research statement for tenure or promotion
Presenters
Cara Frankenfeld, Maine Health Institute for Research
Description
Writing compelling research statements is a critical part of the career trajectory for academic research epidemiologists. A challenge of writing these statements that they will be reviewed by peers inside and outside of the field of epidemiology. Key strategies for crafting messages and telling a cohesive story of participants career trajectories and future plans will be covered. Also as a part of this workshop, participants will outline their research statement and learn key strategies for making their research statements impactful that are independent of specific institutional requirements. Participants in this workshop will also have availability of a one-time review of their statement, within six months of the workshop completion, by an experienced faculty member. This workshop is suitable for academic epidemiologists that are submitting documents for tenure and promotion within 12 months of the workshop completion. The workshop is limited in attendance and, in support of enhancing diversity and equity in epidemiology, priority will be given to individuals who have limited institutional support for writing research statements or having such research statements reviewed internally.
Estimated time distribution:
– Presentation re: research statements structure, goals, and target audiences
– Interactive work drafting outline
– Peer review and discussion
– Review of example statements as a group
– Practical tips on adding impact using quantitative measures
Workshop Details
In Person:
June 10, 2025
5:30pm – 7:30pm
Target Audience: Beginner
Working with unstructured data and text analysis in electronic health records
Presenters
Neal Goldstein, Drexel University Dornsife School of Public Health
Mileana Gianfrancesco, Pfizer,inc.
Description
A wealth of unrealized health information is stored in unstructured fields and datasets, including text found on social media, and clinical note narratives within electronic health records (EHRs). Natural language processing and text analysis techniques allow researchers to operationalize and analyze information beyond what is collected in structured datasets in an efficient manner. These techniques encompass a spectrum from simple string parsing and keyword matching with regular expressions to machine learning models and powerful artificial intelligence solutions. For example, advances and accessibility of large language models have gained attention for their abilities to extract and synthesize vast amounts of text from various domains but require prudent use to minimize potential bias. In this workshop, we will explore: Read more
Virtual-Only Workshops
Workshop Details
Virtual:
July 15, 2025
10:00 AM – 2:00 PM MST
Target Audience: Intermediate
An overview of Difference-in-Difference and Synthetic Control Methods: Classical and Novel Approaches
Presenters
Tarik Benmarhnia, University of California San Diego | Scripps institution of Oceanography
Roch Nianogo, UCLA Fielding School of Public Health
Description
The interest in and use of quasi-experimental methods to evaluate the effect of a health policy or event on a health outcome has drastically increased in the epidemiological literature. Difference-in-differences (DID) and synthetic control (SC) designs exploit the specific timing and place of an intervention implementation as a natural experiment. Canonical versions of such designs have been typically used in settings including one policy/treatment of interest relying on several identification assumptions. In the past few years, recently developed designs based on staggered DID and SC have been proposed to relax several assumptions and handle multiple time periods and exposed units. Read more
Workshop Details
Virtual:
July 8, 2025
10:00 AM – 2:00 PM MST
Target Audience: Intermediate
Systems Science Modeling and Simulation Methods for Epidemiologic Research
Presenters
Roch Nianogo, UCLA | Fielding School of Public Health
Ashley Buchanan, University of Rhode Island
Description
Systems science modeling methods have been used for a long time in various fields, including infectious disease epidemiology, but have only been relatively recently introduced to the broader fields of public health and epidemiology, particularly non-communicable diseases. Yet, despite its tremendous potential and utilization in infectious disease epidemiology, uptake of systems science modeling in public health has been somewhat slow, possibly attributable to a need for training resources. Read more
Workshop Details
Virtual:
July 17, 2025
10:00 AM – 2:00 PM MST
Target Audience: Intermediate
Beyond Confounding: Directed Acyclic Graphs for Risk Management and Collaborative Science
Presenters
Robert Reynolds, Mortality Research & Consulting, inc.
Erik Antonsen, Harvard/MGH, MIT
Steven Day, Mortality Research & Consulting, Inc.
Description
Causal diagrams, most specifically Directed Acyclic Graphs (DAGs), have found extensive use in Epidemiology for the analysis of confounding in causal inference methods. However, DAGs are capable of much more, as they are simultaneously knowledge graphs, network maps, and temporal/structural models of causal events. At the National Aeronautics and Space Administration (NASA), DAGs have become the backbone of the risk management process for the Human Systems Risks of spaceflight. In this session we demonstrate how DAGs can be used to communicate and understand complex risks across scientific domains, and thus enable ongoing scientific collaboration and coordination. We describe how analytic techniques from Network Science can bring insight into the important factors in a causal network, how methods from Psychometrics can infuse regression with causal assumptions, and how computational algorithms from Computer Science enable sophisticated inference – all using a single DAG. Read more
Workshop Details
Virtual:
February, 20 2025
10:00 AM – 2:00 PM MST
Target Audience: Beginner
High-dimensional propensity score and its machine learning extensions in residual confounding control
Presenters
Ehsan Karim, School of Population and Public Health, The University of British Columbia
Description
Are you an epidemiologist or biostatistician seeking to enhance your data analysis skills? Join our workshop focused on high-dimensional propensity score (hdPS) methods and their machine learning extensions. This workshop is designed to help you address residual confounding in observational studies, particularly when dealing with large health datasets such as administrative/survey databases. Read more
Workshop Details
Virtual:
July 10, 2025
10:00 AM – 2:00 PM MST
Target Audience: Intermediate
Writing Reproducible Research with Quarto in R and Python
Presenters
Malcolm Barret, Stanford University
Description
In this workshop, you’ll learn how to use the open-source programming languages R and Python to generate completely reproducible research using Quarto, a modern scientific publishing framework. We’ll focus on how these tools can support academic research and data science, allowing you to iterate between code and results quickly. Read more
Workshop Details
Virtual:
August 5, 2025
10:00 AM – 2:00 PM MST
Target Audience: Beginner
What Would it Take to Change Your Inference? Quantifying the Discourse about Causal Inferences in Epidemiology
Presenters
Kenneth Frank, Michigan State University
Description
Causal inferences are often challenged because of uncontrolled bias. We will turn concerns about potential bias into questions about how much bias there must be to invalidate an inference. For example, challenges such as ‘But the inference of an exposure might not be valid because of pre-existing differences between the treatment groups’ are transformed to questions such as ‘How much bias must there have been due to uncontrolled pre-existing differences to make the inference invalid?’ By reframing challenges about bias in terms of specific quantities, this workshop will contribute to scientific discourse about uncertainty of causal inferences. Read more