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2023 Workshops

SER is pleased to offer the following 2023 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.

Workshop Details

Virtual:
March 1, 2023
12:00 – 4:00pm EST

In Person:
June 13, 2023
5:30pm – 7:30pm

Instructor:
Hailey Banack

Target Audience: Beginner

Developing Competencies for Doctoral Students in Epidemiology

Presenters
Laura Rosella, University of Toronto
Katie Lesko, Johns Hopkins University
Hailey Banack, University of Toronto

Description
The overall objective of this two-part workshop is to develop a set of specific competencies for doctoral students in epidemiology. Competencies refer to a set of topics that doctoral students in epidemiology programs should demonstrate some mastery of prior to completing their training. There exist formal competencies for graduate programs in public health, but there are no standardized criteria for topics to include in doctoral training programs in epidemiology. Read more

“Developing Competencies for Doctoral Students in Epidemiology” is a two part workshop. Part One will be held in a VIRTUAL format on March 1, 2023. Part Two will be held as an IN PERSON workshops on June 13, 2023. Virtual access to part two will not be available.

Workshop Details

Virtual:
April 21, 2023
12:00 – 4:00pm EST

Instructor:
Laura Balzer

Target Audience: Beginner

Introduction to parametric & semi-parametric estimators for causal inference

Presenters
Jennifer Ahern, UC Berkeley
Laura Balzer, UC Berkeley

Description
“This workshop will introduce participants to the Causal Roadmap for epidemiologic questions: 1) clear statement of the research question, 2) definition of the causal model and parameter of interest, 3) assessment of identifiability that is, linking the causal effect to a parameter estimable from the observed data distribution, 4) choice and implementation of estimators including parametric and semiparametric approaches, and 5) interpretation of findings. Read more

Workshop Details

Virtual:
April 24, 2023
12:00 – 4:00pm EST

Instructor:
Chuck Huber

Target Audience: Intermediate

Create Your Own Stata Commands

Presenters
Chuck Huber, StataCorp LLC

Description
“The first half of this workshop will introduce the basics of creating custom Stata commands. You will learn how to store things in memory, where Stata stores things in memory and how to access them, how to handle conditions and branching, and how to use loops. We will then demonstrate how to use these tools with to write custom Stata commands using -program-, -args-, and -syntax-. You will learn how to write commands to perform simple calculations, post-estimation calculations, and create your own graphics commands. Read more

Workshop Details

Virtual:
April 25, 2023
12:00 – 4:00pm EST

Instructor:
Moyses Szklo
Polly Marchbanks

Target Audience: Intermediate

Critical Review and Preparation of Manuscripts Reporting Epidemiologic Findings

Presenters
Moyses Szklo, Johns Hopkins Bloomberg School of Public Health
Polly Marchbanks, American Journal of Epidemiology

Description

In this half-day workshop, participants will critically review a paper as initially
submitted to the American Journal of Epidemiology (AJE), but not yet published. The paper will be sent
to participants in advance of the workshop for their critical review. During the workshop, a
presentation will be made on some of the main points to be considered when preparing or reviewing a
manuscript. Read more

Workshop Details

Virtual:
May 4, 2023
12:00 – 4:00pm EST

Instructor:
Ehsan Karim, The University of British Columbia

Target Audience: Intermediate

High-dimensional propensity score and its machine learning extensions in residual confounding control in pharmacoepidemiologic studies

Presenters
Ehsan Karim, The University of British Columbia

Description
The use of retrospective health care claims datasets is frequently criticized for lacking complete information on potential confounders. Ultimately, the treatment effects estimated utilizing such data sources may be subject to residual confounding. Digital electronic administrative records routinely collect a large volume of health-related information; and many of whom are usually not considered in conventional pharmacoepidemiological studies. Read more



Workshop Details

In Person:
June 13, 2023
8:30 – 12:30pm

Instructors:
Brittany Charlton

Target Audience: Beginner

Mentor Training for Epidemiologists

Presenters
Brittany Charlton, Harvard Medical School/Harvard T.H. Chan School of Public Health

Description
Although mentoring relationships are critical for academic and career success, mentors are often left to learn how to carry out their part in these relationships through trial and error. And yet, there is a growing movement to prepare mentors more deliberately. Read more


Workshop Details

In Person:
June 13, 2023
8:30am – 12:30pm

Instructor:
Laura Balzer

Target Audience: Intermediate

Causal inference for time-varying exposures

Presenters
Lina Montoya, UNC
Laura Balzer, UC Berkeley

Description
This workshop applies the Causal Roadmap to estimate the causal effects with time-vary exposures, 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 maximum likelihood estimation (TMLE) with Super Learner.

Workshop Details

In Person:
June 13, 2023
8:30 – 12:30pm

Instructor:
Kara Rudolph

Target Audience: Intermediate

Modern Causal Mediation Analysis

Presenters
Nima Hejazi, Harvard
Ivan Diaz, NYU
Kara Rudolph, Columbia University

Description
Causal mediation analysis can provide a mechanistic understanding of how an exposure impacts an outcome, a central goal in epidemiology and health and social sciences. However, rapid methodologic developments coupled with few formal courses presents 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.

Workshop Details

In Person:
June 13, 2023
8:30 – 12:30pm

Instructor:
Neal Goldstein

Target Audience: Beginner

Epidemiological analysis of electronic health records

Presenters
Milena Gianfrancesco, Pfizer, Inc.
Neal Goldstein, Drexel University

Description
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.

Workshop Details

In Person:
June 13, 2023
8:30 – 12:30pm

Instructor:
Tyler VanderWeele

Target Audience: Intermediate

Interaction Analysis

Presenters
Tyler VanderWeele, Harvard University

Description
This workshop will provide a broad introduction to the topic of interaction. We will discuss interaction on additive and multiplicative scales, and their relation to statistical models (e.g. linear, log-linear and logistic models). Read more


Workshop Details

In Person:
June 13, 2023
1:00 – 5:00pm

Instructor:
Aayush Khadka

Target Audience: Beginner

A Primer on Quantile Regression for Epidemiologists

Presenters
Anusha Vable, University of California, San Francisco
Jillian Hebert, University of California, San Francisco
Aayush Khadka, University of California, 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 means, which are more common in the epidemiological literature. However, quantile regression remains underused in epidemiology.  Read more


Workshop Details

In Person:
June 13, 2023
1:00 – 5:00pm

Instructor:
Marynia Kolak

Target Audience: Beginner

Intro to Spatial Analysis & GIS for Spatial Epidemiology in R

Presenters
Marynia Kolak, University of Illinois

Description
Measurements of neighborhood social determinants of health are increasingly urgent in modern public health thinking, and are thought to drive and/or reinforce racial, social, and spatial inequities. Sometimes this necessitates an investigation of neighborhood health patterns, like premature mortality at the census tract scale. Sometimes we’re interested in area factors like poverty, access to affordable housing, distance to the nearest health provider, or polluting factories — and how these factors magnify, moderate, or mediate individual level health. 

Workshop Details

In Person:
June 13, 2023
1:00 – 5:00pm

Instructor:
Jennifer Loukissas

Target Audience: Beginner

Media Training: Skills for Communicating Research Findings

Presenters
Jennifer Loukissas, National Cancer Institute

Description
*This workshop is designed for epidemiologists at all career stages.*

The skills needed to effectively communicating research findings require training and practice. This workshop will help epidemiologists improve their ability to effectively communicate their research findings to the media, and through them to the public and specific audiences, such as clinicians, public health practitioners, and other researchers. While this workshop will focus on basic skills of communicating to the media, the skills can also be applied when disseminating information to community partners and other audiences.

Workshop Details

In Person:
June 13, 2023
1:00am – 5:00pm

Instructor:
Louisa Smith

Target Audience: Intermediate

Reproducible Epidemiology in R

Presenters
Louisa Smith, Northeastern University

Description
Have you ever painstakingly copied and pasted output into individual table cells, only to find yourself starting from scratch when you receive an updated dataset from your collaborators? Have you sat twiddling your thumbs while rerunning all of your analyses just because you added a single covariate to a regression model?  In this workshop, we will learn techniques for avoiding these frustrating, slow, and error-prone processes. We will focus on conducting reproducible analyses using the targets package in R and on creating reproducible documents using RMarkdown and/or Quarto. Read more


Workshop Details

In Person:
June 13, 2023
1:00 – 5:00pm

Instructors:
Paul Zivich

Target Audience: Intermediate

The ABC's of M-estimation

Presenters
Rachael Ross, University of North Carolina at Chapel Hill
Stephen Cole, University of North Carolina at Chapel Hill
Paul Zivich, University of North Carolina at Chapel Hill

Description
M-estimation is a generalization of maximum likelihood that allows a set of estimating equations to be stacked together and can be used for a variety of epidemiologic measures. Importantly, M-estimators offer a simple way to estimate the variance for complicated measures. Read more


Workshop Details

In Person:
June 13, 2023
5:30 – 7:30pm

Instructor:
Ian Shrier

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, Lady Davis Institute, 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 13, 2023
5:30 – 7:30pm

Instructor:
Jennifer Cruz

Target Audience: Beginner

Positionality for Epidemiologists: Exploring the Role of Our Social Identities in Quantitative Research

Presenters
Jennifer Cruz, Harvard T.H. Chan School of Public Health
Shoba Ramanadhan, Harvard T.H. Chan School of Public Health
Jarvis Chen, Harvard T.H. Chan School of Public Health 

Description
Who we are, who we are in community with, and where we are from all play a role in the science we do- from the research questions we ask to the evidence we use to back our claims. Positionality refers to how our social identities and lived experiences not only influence the choices we make throughout the research process but also how those factors shape how others view us, our work, and the power we hold in a specific research context.

Workshop Details

In Person:
June 13, 2023
5:30 – 7:30pm

Instructor:
Mike Jackson

Target Audience: Beginner

How to make a picture worth a thousand words: Effectively communicating your research results using statistical graphics

Presenters
Mike Jackson, EpiAssist, LLC

Description
Epidemiologists can use statistical graphics to understand our data and to guide us toward correct inferences. Well-designed graphics can also be powerful tools for communicating our study findings. However, while statistical software makes it easy to produce certain types of figures, the default options leave much to be desired. Read more


Workshop Details

In Person:
June 13, 2023

5:30 – 7:30pm

Instructor:
Gesulla Cavanaugh

Target Audience: Beginner

Eye-Tracking Data Analysis for Epidemiological Context

Presenters
Gesulla Cavanaugh, Nova Southeastern University

Description
Eye-tracking data have grown in popularity in behavioral studies but have recently gained traction in other fields, such as neuroscience and education. While their use in epidemiological studies is underexplored, they are value-adding components for various epidemiological models. Read more


Workshop Details

In Person:
June 13, 2023
1:00pm – 5:00pm

Virtual:
May 2, 2023
10:00am – 2:00pm MT

Instructor:
Malcom Barrett

Target Audience: Intermediate

Writing Reproducible Research in R with Quarto

Presenters: 
Malcolm Barrett, Posit

Description
In this workshop, you’ll learn how to use the R programming language 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

In Person:
June 13, 2023
8:30am – 12:30pm

Virtual:
May 16, 2023, 2022
12:00 – 4:00pm EST

Instructors:
Steve Mooney

Target Audience: Beginner

R for Epidemiologists

Presenters
Steve Mooney, University of Washington

Description
This workshop will introduce participants to the R statistical computing platform for use in epidemiologic analysis. It is not intended to transform untested novices into R wizards in a mere half-day; rather, the goal will be to introduce the conceptual underpinnings, tools, and external resources that participants will need to overcome barriers to using R that they might encounter on their own, later.

Workshop Details

In Person:
June 13, 2023
1:00pm – 5:00pm

Virtual:
July 6, 2023
12:00 – 4:00pm EST

Instructors:
Jessica Young

Target Audience: Intermediate

Causal Inference and Competing Events

Presenters
L. Paloma Rojas-Saunero, UCLA
Jessica Young, Harvard Medical School
Mats Stensrud, EPFL, Lausanne

Description
A competing risk event is any event that ensures the outcome of interest cannot subsequently occur. For example, in a study where prostate cancer death is the primary outcome, a fatal stroke is a competing event because an individual cannot die of cancer once they have died of stroke. When competing events are present, many possible definitions of a causal effect may be considered. Read more


Workshop Details

Virtual
July 7, 2023
12:00 – 4:00pm EST

Instructors:
Roch Nianogo

Target Audience: Beginner

An overview of Difference-in-Difference and Synthetic Control Methods: Classical and Novel Approaches

Presenters
Tarik Benmarhnia, University of California San Diego
Roch Nianogo, University of California, Los Angeles

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.

Workshop Details

Virtual:
July 18, 2023
12:00am – 4:00pm EST

Instructors:
Kenneth Frank

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. There may be bias due to uncontrolled confounding variables or non-random selection into a sample. 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. Critically, the approaches presented in this workshop based on correlations of omitted variables and the replacement of cases have strong intuitive appeal. In part I, we use Rubin’s causal model to interpret how much bias there must be to invalidate an inference in terms of replacing observed cases with counterfactual cases or cases from an unsampled population. This is extended to logistic regression. In part II, we quantify the robustness of inferences in terms of correlations associated with unobserved variables. Calculations will be presented using the open-source app http://konfound-it.com with links to R and Stata modules. The format will be a mixture of presentation and individual hands-on exploration as well as group work.