The APS Annual Convention includes these extended educational sessions that offer attendees the opportunity to learn research methods and techniques from prominent psychological scientists.

Workshops are open to Convention registrants only and require additional registration fees. Workshops can be added when you register for the APS Convention. If you’ve finalized your registration, please follow these instructions to add a workshop.

THURSDAY, MAY 23

Introduction to Structural Equation Modeling in the Psychological Sciences

Presenter: Tim Hayes, Florida International University

Thursday, May 23, 9:00 AM – 12:50 PM  

Structural Equation Modeling (SEM) combines common factor analysis with multiple regression to allow researchers to assess true score relations among constructs of theoretical interest. This workshop presents an overview of the logic, implementation, and interpretation of SEMs. Topics covered include: path analysis, confirmatory factor analysis, and structural regression analysis. 

Measurement, Not Schmeasurement

Presenter: Jessica Flake, McGill University

Thursday, May 23, 9:00 AM – 12:50 PM  

We assume that psychological measures produce meaningful numbers: higher satisfaction scores indeed represent more satisfaction. Measurement is a fundamental part of psychological research, and our scores require thorough and transparent evaluation of their validity. This workshop will cover how to evaluate and refine scales using psychometric methods and open science practices.

Understanding Bayesian: An Introduction to Key Concepts

Presenter: Brian Leventhal, Jame Madison University

Thursday, May 23, 9:00 AM – 12:50 PM  

This workshop introduces steps of Bayesian analysis:

• specifying a prior
• using a likelihood
• forming a posterior
• making inferences

Attendees will be able to articulate major considerations of a Bayesian analysis, contrast Bayesian and Frequentist approaches, and identify components of Bayesian research.

Data Visualization in R for Researchers Who Do Not Use R

Presenters: Emily Nordmann, University of Glasgow and Wilhelmiina Toivo, University of Glasgow

Thursday, May 23, 1:00 PM – 3:50 PM  

In this session we’ll cover why you should use R for data visualization followed by an introduction to boxplots, histograms, violin-plots, density plots, bar charts, scatterplots, and more complex layered plots using ggplot. No prior knowledge of R is required.

Dynamic Structural Equation Modeling (DSEM) in Mplus

Presenter: Ellen Hamaker, Utrecth University

Thursday, May 23, 1:00 PM – 4:50 PM           

This workshop provides a first introduction—both theoretically and practically—into dynamic structural equation modeling (DSEM). DSEM combines time series analysis, multilevel modeling, and structural equation modeling, and allows for a flexible and elegant approach to intensive longitudinal data such as obtained with daily diaries, experience sampling, and ambulatory assessments.

Power Analysis in Structural Equation Modeling (SEM)

Presenter: Y. Andre Wang, University of Toronto

Thursday, May 23, 1:00 PM – 4:50 PM    

This workshop will introduce attendees to power analysis in SEM and offer a hands-on tutorial. Attendees will learn how to connect power considerations (e.g., to detect specific target effects, to assess model fit) to their research goals, and how to conduct power analysis on their own models using R or pwrSEM, a point-and-click web application.

FRIDAY, MAY 24

Introduction to Generalized Linear Models in the Psychological Sciences

Presenter: Connor McCabe, University of Washington

Friday, May 24, 10:30 AM – 11:50 AM

This workshop provides a comprehensive introduction to generalized linear models (GLMs), a popular approach for modeling binary and count dependent variables in psychological science. It will provide accessible coverage of both theory and application, including hands-on demonstrations for data analysis and visualization in R and state-of-the-science methods for moderation analysis.

Prerequisite:

• Bring a laptop (fully charged) with R and Rstudio. (optional)
• A working knowledge of linear regression principles and at least some familiarity with the R statistical software language.

Experience Sampling Methods and Implementation

Presenter: Sabrina Thai, Brock University

Friday, May 24, 10:30 AM – 12:20 PM

Learn how to create your own experience-sampling smartphone app using ExperienceSampler, and how to integrate ExperienceSampler with existing survey software. We will also discuss issues related to conducting experience sampling studies: design decisions, best practices, data organization, and data analysis. 

Prerequisite:  

• Bring your laptops (fully charged) to follow along with the workshop slides.

A Beginner’s Guide to Qualitative Research

Presenter: Jaclyn Siegel, The University of Chicago

Friday, May 24, 10:30 AM – 12:20 PM

This beginner-friendly workshop will lead researchers through some of the basics of conducting qualitative research (e.g., different analytic methods, positionality), including practical elements of qualitative work (e.g., sample sizes). The workshop will end with a deep dive into thematic analysis, a popular approach to analyzing qualitative data in psychology. 

Prerequisite: none

Creating Computationally Reproducible Manuscripts – CANCELLED

Presenter: Jason Geller, Princeton University

Friday, May 24, 1:00 PM – 2:20 PM

This workshop provides a comprehensive introduction to generalized linear models (GLMs), a popular approach for modeling binary and count dependent variables in psychological science. It will provide accessible coverage of both theory and application, including hands-on demonstrations for data analysis and visualization in R and state-of-the-science methods for moderation analysis.

Open Science practices, which emphasize transparency, reproducibility, and accessibility, are indeed becoming increasingly important in the psychological community. In this workshop, you will learn to set up a reproducible workflow to create a publication-ready manuscript that combines data, R or Python code, text, and references.  

Prerequisites:

• R/Rstudio 
• Quarto
• Basic knowledge of R or Python

Introduction to Multilevel Modeling

Presenter: Jason Rights, The University of British Columbia

Friday, May 24, 1:00 PM – 2:50 PM

Multilevel modeling (MLM) is widely used in psychology and other fields to analyze nested data structures (e.g., students nested within schools or repeated measures nested within individuals). This workshop will provide a brief introduction to MLM, including both theoretical foundations as well as tools for practical application.

Prerequisite:

• Knowledge of regression modeling
• Bring a laptop (fully charged) with R & Rstudio installed – (optional)

SATURDAY, MAY 25

Writing for a Popular Audience to Disseminate Your Work and Broaden Your Impact

Presenter: Andrew Devendorf, University of South Florida

Saturday, May 25, 10:30 AM – 11:50 AM

Although psychologists can benefit society by sharing their research with the public, most lack training on translating ideas into an accessible, engaging, and meaningful package. This workshop will overview the process of writing for, and pitching to, the popular press. Strategies and challenges related to scientific communication will be discussed.    

Data Storytelling Training

Presenter: Lisa Cantrell, Stories of Science

Saturday, May 25, 1:00 PM – 2:20 PM

How do you make a research presentation compelling? One of the biggest secrets in science communication is this: the same narrative strategies that Hollywood uses for creating compelling movies are those that we should be using to talk about our research findings.  In this workshop, participants experience demos of research presentations told with and without storytelling components and then discuss how a story format pushes the audience’s thinking forward about the research. 

Participants will have the opportunity to practice sharing their data story in small groups and by the end of the session, participants will have a draft of their own research data story and a method for turning their future studies into data stories for presentations at conferences, job talks, and speaking engagements.

The Art of the Elevator Pitch

Presenter: Tammy Spence, Stories of Science

Saturday, May 25, 2:30 PM – 3:50 PM

The elevator pitch. We talk about it often. We say it is important for networking and sharing our research. And yet when it comes to actually doing it, we find ourselves using jargon, spending too much time on details that aren’t important, or not giving the right context for our audience. The elevator pitch is, at its core, a story that should be compelling, focused, and clear. 

This workshop is intended to guide participants step by step through building their own compelling, clear, and focused elevator pitch—specifically around their research—and then honing it to 60 seconds. By the end of the session, participants will have a draft of a 60-second elevator pitch and 1-2 short anecdotes that they can use to illustrate their research.