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.

Rates
APS Members: $75
APS Student Members: $25

You may add a workshop to your registration on-site!

Please visit the Registration Desk for more information.

Thursday, May 26 

Introduction to Exploratory Graph Analysis (EGA) with R: A Modern Network Psychometrics Approach to Structural Validity, Item, Dimension Analysis, and Beyond   

Hudson Golino and Laura Jamison, University of Virginia 

Thursday, May 26, 9:00 AM – 12:50 PM, Grand Hall J 

This course is a hands-on introduction to exploratory graph analysis (EGA) using R, with the following topics: (a) dimensionality assessment, (b) item and dimension stability, (c) fit indices based on quantum information theory, (d) measurement invariance, and (e) dynamic EGA for (intensive) longitudinal data and for analyzing latent topics in social media posts. 

Prerequisites: Attendees should have a basic knowledge of R and RStudio and install the software on your laptops.   

The General Linear Model: A Flexible Tool for Analyzing Psychological Data   

Masumi Iida, Arizona State University  

Thursday, May 26, 9:00 AM – 12:50 PM, Grand Hall I 

 In this 4-hour workshop, participants will learn the general overview of general linear model, which is a foundation for data analytic approaches in psychology. The workshop will cover bivariate regression, multiple regression, and analysis of variance (ANOVA) from the modeling framework. 

Prerequisites: Laptops are required.   

Experience Sampling Methods and Implementation   

Sabrina Thai, Brock University  

Thursday, May 26, 9:00 AM – 12:50 PM, Michigan 1ABC  

This hands-on workshop demonstrate how to create your own experience-sampling smartphone app, using ExperienceSampler, and how to integrate ExperienceSampler with existing survey software. The workshop will also discuss issues related to conducting an experience sampling studies: design decisions, best practices, data organization, and data analysis. 

 Prerequisites: Laptops are required to download and access resources. 

Introduction to Sample-Size Planning for Power and Accuracy 

Samantha F. Anderson, Arizona State University   

Thursday, May 26, 2:00 – 4:20 PM, Grand Hall J 

Learn how to plan appropriate sample sizes for analysis of variance and linear regression designs. We will focus on three types of approaches: (a) planning for power using the minimally interesting effect size, (b) planning for power using prior literature, and (c) planning for accuracy. Demonstrations using freely available software are included. 

 Prerequisites:  

1. Laptops are recommended. 
2. Previous introductory graduate-level (or upper-level undergraduate) statistics course in ANOVA and/or regression.  
3. Please install the following software:  G*Power: https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower.html  R: https://www.r-project.org/  

Introduction to Structural Equation Modeling in the Psychological Sciences   

Timothy Hayes, University of Southern California 

Thursday, May 26 1:30 – 5:20 PM, Grand Hall I  

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 SEM. Topics covered include path analysis, confirmatory factor analysis, and structural regression analysis. No background experience is necessary, although participants opting to use R are encouraged to have some background experience with it.  There won’t be time to teach R basics. 

 Prerequisites: 

1. Attendees should have taken a standard graduate course in linear regression analysis.   
2. Download lavaan package in R in advance to participate in the data analysis exercise.   
3. Laptops are recommended. 

Sunday, May 29

Teaching Statistics Using JASP   

Eric-Jan Wagenmakers, University of Amsterdam 

Sunday, May 29, 9:00 – 10:50 AM, Regency A  

This workshop will demonstrate the functionality of the open-source JASP statistical software program (jasp-stats.org), with an emphasis on recently developed tools for teaching statistics. 

 Prerequisites: Laptops are required and should have the latest version of JASP – jasp-stats.org.  

Modern Missing Data Analyses   

Craig K. Enders, University of California, Los Angeles 

Sunday, May 29, 9:00 – 11:50 AM, Regency C  

This workshop will provide participants with a gentle introduction to Bayesian estimation and multiple imputation. The presentation will include a mix of foundational material and computer applications. Course content will be accessible to attendees with a foundation in multiple regression.   

Prerequisites: Laptops are recommended but optional. 

Introduction to Multilevel Modeling   

Jason D. Rights, The University of British Columbia  

Sunday, May 29, 11:00 AM – 12:50 PM, Regency A  

 Multilevel Modeling (MLM) is widely used in psychology and other fields to analyze nested data structures (e.g., students nested within schools). This workshop will provide a brief introduction to MLM, including both theoretical foundations as well as tools for practical application. Attendees will ideally have prerequisite knowledge of regression modeling. 

Prerequisites: Attendees are encouraged to bring a laptop and install R and Rstudio to take notes and run sample R scripts.