M3_2024_Preliminary_Program_03-30-2024
Monday, June 24th
Pre-Conference Workshop – Sacha Epskamp
9:00 am – 5:00 pm
Network Psychometrics with psychonetrics in R
Sacha Epskamp
The freely available psychonetrics package for R provides an encompassing framework for psychometric network modeling, combining typical practices in Structural Equation Modeling (SEM) with undirected network modeling now commonly used in network psychometrics. The psychonetrics package can be used for various types of data (cross-sectional, time-series and panel data), and not only allows researchers to explore relations between observed and latent variables through the use of network models, but also allows researchers to perform confirmatory tests on given network structures and to test for homogeneity in (latent) network structures across groups.
This workshop will introduce participants to the psychonetrics package and will teach participants to:
– interpret undirected multivariate network models
– understand differences between within- and between-person effects and cross-sectional and longitudinal data
– install, load and use the psychonetrics package
– use psychonetrics for exploratory network estimation (from cross-sectional, N=1 time-series and panel data)
– use psychonetrics for confirmatory network testing
– use psychonetrics to combine latent variable models with network models
– use psychonetrics for multi-group invariance and homogeneity testing
Familiarity with R and having R and the psychonetrics package installed are recommended for attending the workshop.
Bio: Sacha Epskamp is an associate professor at the National University of Singapore, Department of Psychology. Previously, he worked at the University of Amsterdam in the Department of Psychology and the Centre for Urban Mental Health. In addition, Sacha Epskamp is a former research fellow at the Amsterdam Institute for Advanced Studies and has been a visiting researcher at the Complexity Institute of Nanyang Technological University. In 2016, Sacha Epskamp completed his seminal PhD on network psychometrics—estimating network models from psychological datasets and equating these to established psychometric modeling techniques. This dissertation laid the groundworks for the field of Network Psychometrics. He has implemented these methods in several software packages now routinely used in diverse fields of psychological research. Sacha Epskamp teaches multivariate statistics and data science, and his research interests involve (network) psychometrics, meta-science, reproducibility, complexity, time-series modeling, and dynamical systems modeling. Sacha Epskamp has received several awards for his research, including the Leamer-Rosenthal Prize of the Berkeley Initiative for Transparency in the Social Sciences, the dissertation prize of the psychometric society, and the junior scientific award of the Complex Systems Society.
Tuesday, June 25th
Continental Breakfast and Registration 7:30 – 8:30 am
McHugh Hall Atrium
Opening Keynote – Denny Borsboom 8:40 – 10:10 am
McHugh Hall 102
The Nature of the Measurement Game: Psychological Constructs as Complex Systems
In psychology, the relation between observables and theoretical constructs has traditionally been conceptualized in terms of measurement: observables (e.g., symptoms like self-reproach and suicidal ideation) are viewed as noisy measures of a latent psychological construct that acts as a common cause (e.g., major depression). Important psychometric models, such as the Item Response Theory model and the Factor Analysis model, represent this hypothesis in a statistical structure, which allows researchers to evaluate the tenability of their measurement hypothesis by fitting the model to data. In the past decade, I have investigated an alternative way of thinking, in which observables are not indicators of a latent construct, but interact with one another in a complex system; for instance, the symptom of self-reproach may facilitate suicidal ideation quite independently of whether any latent construct of depression exists or not. Such interactions can statistically be represented in a network model, which allows one to translate the abstract theory into a concrete statistical structure. The development of these models has accelerated in the past decade, and they have become popular in various subdomains of psychology. In this talk, I will discuss these models from a psychometric perspective, and evaluate their plausibility as alternatives to traditional measurement models. I will argue that network approaches fundamentally change the nature of the measurement game, and that we have only just begun to evaluate the consequences of these changes.
10:10 – 10:30 am Break – McHugh Hall Atrium
Concurrent Paper Session 1 Tuesday 10:30 am – 12:00 pm
Session 1A: Disaggregating Level-Specific Effects and Quantifying Explained Variance in Cross-Classified Multilevel Models
Room TBA
| Paper | Authors |
| Disaggregating Level-Specific Effects and Quantifying Explained Variance in Cross-Classified Multilevel Models | Jason D. Rights |
Session 1B: Modeling Spatial Data
Room TBA
| Paper | Authors |
| A New Way of Analyzing Malaria Data: A Non-Stationary Geostatistical Modeling Approach | Bedilu Alamirie Ejigu Paula Moraga |
| Modern Spatial Path Analytic Tools to Investigate the Geography of Medical Debt across a US State | Emil Coman Samuel Bruder Corey Grantham |
| Investigating the Life Expectancies Differences in the US by Comparing Naïve and Spatial Analytic Methods across Census Tracts, Counties, and States | Emil Coman Jason Byers Blair Johnson Sandro Steinbach Peter (Xiang) Chen Stewart Fotheringham |
Session 1C: Measurement Invariance and Moderation
Room TBA
| Symposium | Authors |
| Invariance: What Does Measurement Invariance Allow Us to Claim? | John Protzko |
| A Simulation Study of Alignment Structure Equation Modeling in Assessing Measurement Invariance with Bi-factor Models | Qingzhou Shi Joni M. Lakin Chunhua Cao |
| Modeling Construct Change Over Time Amidst Potential Changes in Construct Measurement: A Longitudinal Moderated Factor Analysis Approach | Siyuan Marco Chen Daniel J. Bauer |
Session 1D: Advances in Mixture Modeling
Room TBA
| Paper | Authors |
| Bias-Correction and Robustness for the Latent Profile Transition Analysis with Random Intercepts and Auxiliary Variables: Simulation and Empirical Analyses | Hawjeng Chiou Ming-Chi Tseng Pi-Fang Lin |
| Signals of Uncertainty and Misspecification in Latent Class Analysis | Zachary Collier Joshua Sukumar |
| Evaluating Bayesian Transition Diagnostic Classification Models for Reporting Within-Year Progress | Jeffrey C. Hoover W. Jake Thompson |
Lunch Tuesday 12:00 – 1:10 pm
Student Union Ballroom
3rd floor, Student Union
Concurrent Paper Session 2 Tuesday 1:10 – 2:10 pm
Session 2A: Multilevel R-squared Effect Size Measures and Bootstrapped Confidence Intervals
Room TBA
| Paper | Authors |
| Multilevel R-squared Effect Size Measures and Bootstrapped Confidence Intervals | Mairead Shaw Jason D. Rights Jessica Kay Flake |
Session 2B: Refining Mediation Analysis in Latent Growth Models
Room TBA
| Paper | Authors |
| Refining Mediation Analysis in Latent Growth Models with Sensitivity to Omitted Confounders | Davood Tofighi |
Session 2C: nMAX: Restoring Caution and Integrity to the Power Analysis Process
Room TBA
| Paper | Authors |
| nMAX: Restoring Caution and Integrity to the Power Analysis Process | Greg Hancock Yi Feng |
Session 2D: Dealing with Missing Data
Room TBA
| Paper | Authors |
| Comparing Alternatives to the Three-Form Planned Missing Data Design | Alexander M. Schoemann E. Whitney Moore Emily M. Meier Kelly L. Reburn Mark C. Bowler |
| Estimating the Average Treatment Effect in Longitudinal Randomized Controlled Trials with Missing Data: Will It Help to Add a Quadratic Term? | Manshu Yang Lijuan Wang Scott E. Maxwell |
2:10 – 2:30 pm Break – McHugh Hall Atrium
Concurrent Paper Session 3 Tuesday 2:30 – 3:30 pm
Session 3A: Innovations in Longitudinal Analysis
Room TBA
| Paper | Authors |
| An Estimation Approach for Time-Varying Effect Models Using Cubic Splines | Jingwei Li Donna Coffman Megan E. Piper |
| Deriving Models of Change with Interpretable Parameters: Linear Estimation with Nonlinear Inference | Ethan McCormick |
Session 3B: Machine Learning and Modeling
Room TBA
| Paper | Authors |
| Machine Learning Structural Equation Modeling and Falsificatory Data Analysis | Michael Truong Ji Yeh Choi |
| Unsupervised Survey Bot Detection: In Search of High Classification Accuracy | Carl F. Falk Amaris Huang Michael J. Ilagan |
Session 3C: Multilevel Modeling in Stata: A Teaching Demonstration
Room TBA
| Paper | Authors |
| Multilevel Modeling in Stata: A Teaching Demonstration | Meghan Cain |
Session 3D: Understanding Composite-Based Methods via Regression Component Analysis
Room TBA
| Symposium | Authors |
| Understanding Composite-Based Methods via Regression Component Analysis | Edward Rigdon |
Session 3E: Issues in Factor Analysis
Room TBA
| Paper | Authors |
| How Many Factors? Comparing Factor Retention Criteria in Exploratory Factor Analysis | Briana Oshiro D. Betsy McCoach Jessica Kay Flake |
| Fitting CFA Models with a Mixture of Continuous and Categorical Observed Variables | Christine DiStefano Dexin Shi Guyin Zhang |
3:30 – 3:50 pm Break
Concurrent Paper Session 4 Tuesday 3:50 – 4:50 pm
Session 4A: A Framework for Modeling Dyadic Discrepancy
Room TBA
| Paper | Authors |
| A Framework for Modeling Dyadic Discrepancy | Robert E. Wickham Kathryn S. Macia |
Session 4B: Graphical Modeling
Room TBA
| Paper | Authors |
| EDA-graph: Graph Signal Processing of Electrodermal Activity for Emotional States Detection | Luis Roberto Mercado Diaz Yedukondala Rao Veeranki Fernando Marmolejo-Ramos Hugo F. Posada-Quintero |
| Application of Gaussian Graphical Models to Visualization and Prediction of Assessment Outcomes | James J. Thompson |
Session 4C: Factor Models for Dynamics
Room TBA
| Paper | Authors |
| Factor Analysis for Topological Equivalence (FATE): Innovating Factor Analysis for Dynamic Constructs | Pascal Deboeck Jonathan E. Butner Ascher K. Munion Brian R.W. Baucom R. Chris Fraley Omri Gillath |
| Bayesian Estimation of Factor Models characterizing Dynamics | Ascher Munion Pascal Deboeck Jonathan Butner |
Session 4D: Advances in Modeling for Causal Inference
Room TBA
| Paper | Authors |
| Exploring Model-Based Causes for Effect-Size Shrinkage in Educational Research | M. Shane Tutwiler Michael Carlozzi Zoe Kao |
| Evaluating the Impact of Analytic Approaches in a Multilevel Regression Discontinuity Application | Jason Schoeneberger Christopher Rhoads Faeze Safari |
Session 4E: Tools for Teaching Multilevel Modeling
| Paper | Authors |
| Using R to enhance shared understanding of linear mixed effect models with and without data across disciplines | Katherine Zavez Ofer Harel |
| A Communication-focused Approach to Building Path Diagrams for Multilevel Models | Jeffrey M. Girard |
Poster Session and Reception
Student Union Ballroom
5:00 – 7:00 pm
Tuesday, June 25th
Third Floor, Student Union
Wednesday, June 26th
Continental Breakfast
8:30 – 9:00 am
McHugh Hall Atrium
Concurrent Paper Session 5 Wednesday 9:00 – 10:00 am
Session 5A: Dealing with Daily Data
Room TBA
| Paper | Authors |
| How We Cycle: A Tutorial on Combining Day-to-Day Dynamics with Day-of-Week Effects and Weekly Dynamics | Mohammadhossein (Manuel) Haqiqatkhah Ellen L. Hamaker |
| Generalizability Theory Applied to Daily Relationship Quality: Substantive and Statistical Directions | Madison Shea Smith Susan C. South |
Session 5B: Variable Selection in Building Generalized Linear Mixed Models
Room TBA
| Paper | Authors |
| A New Algorithm for Variable Selection in Building Generalized Linear Mixed Models | Yutian T. Thompson Yaqi Li Hairong Song David E. Bard |
| A New Method for Variable Selection in Building GLMMs with Incomplete Data | Yutian T. Thompson Yaqi Li David E. Bard |
Session 5C: Simplifying SEM with Shortcut Wizardry
Room TBA
| Paper | Authors |
| Simplifying SEM with Shortcut Wizardry | Laura Castro-Schilo |
Session 5D: Disentangling Person-Dependent and Item-Dependent Causal Effects
Room TBA
| Paper | Authors |
| Disentangling Person-Dependent and Item-Dependent Causal Effects: Applications of Item Response Theory to the Estimation of Treatment Effect Heterogeneity | Joshua Gilbert Luke Miratrix Mridul Joshi Benjamin Domingue |
10:00 – 10:20 am Break –McHugh Hall Atrium
Concurrent Paper Session 6 Wednesday 10:20 – 11:50 am
Session 6A: Bayesian Models
Room TBA
| Paper | Authors |
| Comparing the Accuracy of Three Predictive Information Criteria for Bayesian Linear Multilevel Model Selection | Sean Devine Carl F. Falk Ken A. Fujimoto |
| Modeling Misspecification as a Parameter in Bayesian Structural Equation Models | James Uanhoro |
| Bayesian Semiparametric Item Response Theory Models: A Methodological Illustration | Meng Qiu Sally Paganin |
Session 6B: Novel Applications of Latent Variable Modeling
Room TBA
| Paper | Authors |
| Decomposing the Effects of Suffering on Depression Using a Reparameterized SEM and Penalized Maximum Likelihood | Noah Padgett Richard Cowden Tyler J. VanderWeele |
| Intensive Longitudinal Modeling of Big Social Media Data | Jeffrey M. Girard |
| Validation of the Evidence-Based Practices Attitudes Scale (EBPAS) using Dynamic Fit Index Cutoffs | Julian M. Hernandez-Torres Natalia Giraldo-Santiago Daniel McNeish |
Session 6C: Reproducibility, Replicability, and Registration of Simulation Studies
Room TBA
| Paper | Authors |
| Why Do Reproducibility and Replicability of Simulation Studies Matter? | Jessica Kay Flake |
| Replicating Simulation Research: A Case Study | Tristan D. Tibbe |
| Registered Reports for Simulation Studies | Amanda Kay Montoya |
| How to Register Your Simulation Study: Our Lessons Learned | Lindsay Alley Mairead Shaw |
Session 6D: Missing Data: Problems and Solutions
Room TBA
| Paper | Authors |
| Evaluating the Effect of Change on Change in Cross-Domain Latent Growth Curve Analysis with Missing Data | Parisa Rafiee Manshu Yang |
| A Solution for Including Auxiliary Variables with Categorical Dependent Variable Estimation in SEM | Mallory R. Kroeck Brian T. Keller Nicholas A. Smith |
| Dummy Variable Adjustment Technique: An Alternative to Maximum Likelihood and Multiple Imputation | Roula Aldib Lee Branum-Martin |
Lunch Wednesday 12:00 – 1:00 pm
Student Union
Please be sure to return your lunch card!
Please note: Dining cards can be used only on Wednesday, June 26th and only at the Union Street Marketplace. When you return your dining cards, be sure to hand them to a member of the conference staff so they can cross your name off the list. Please do not just leave it on the registration table—those who return their cards will be entered in a raffle to win a free conference registration for the 2025 conference.
Concurrent Paper Session 7 Wednesday 1:00 – 2:30 pm
Session 7A: Modeling Individual Differences
Room TBA
| Paper | Authors |
| Measurement Invariance of the Big Five across Socioeconomic Background: Multigroup Confirmatory Factor Analysis and Alignment Optimization | Emilija Meier-Faust Sandra Bohmann |
| Examining Response Styles and Their Impact on Psychological Testing Outcomes: A Mixture IRT Modeling Approach | Fatih Ozkan |
| Applying SEM Based Person-Fit to the Wechsler Adult Intelligence Scale IV Demonstrate the Validity of Measurement at the Individual Level | Jared Block Steven Reise |
Session 7B: Network Applications
Room TBA
| Paper | Authors |
| Exploring the Emotional Well-Being of Young Adults through Network Psychometrics | Daniel Hernández-Torrano |
| Exploring the Dynamics of Motivation in Physical Activity among Older Adults Through Panel Network Approach | Tommaso Palombi Denny Borsboom René Freichel Elisa Cavicchiolo Fabio Lucidi Fabio Alivernini |
| Estimating the Group Differences of Longitudinal Network Analysis: A Example of Eating Disorder Psychopathology | Jihong Zhang Jinbo He |
Concurrent Paper Session 7 Wednesday 1:00 – 2:30 pm
Session 7C: Advances in Multilevel Mixture Modeling
Room TBA
| Paper | Authors |
| Examining the Effect of Nested Data on Class Enumeration and Model Fit in Latent Profile Analysis | Angela Starrett Katherine Masyn |
| Application of a Multilevel Latent Class Analysis with Cross-Classified Data | Audrey Leroux Katherine Masyn |
| Moderated Nonlinear Mixture Analysis for Longitudinal Invariance Testing in Latent Transition Analyses | Katherine Masyn Boshi Wang |
Session 7D: Structural Equation Modeling Methods
Room TBA
| Paper | Authors |
| Comparing Approaches to Examine Multiple Binary Moderators in Latent Variable Models | Kaylee Litson Amanda Kay Montoya Yiwei Wang |
| Quantile Structural Equation Modeling: Testing a Novel Distance Based Approach | Jeffrey Shero Zhixin Zhu Jessica Logan |
2:30 – 3:00 pm Break – Ice Cream in McHugh Atrium
Concurrent Paper Session 8 Wednesday 3:00 – 4:00 pm
Session 8A: Innovations in Mixed Modeling
Room TBA
| Paper | Authors |
| Model Selection of GLMMs in the Analysis of Count Data in SCEDs: A Monte Carlo Simulation | Haoran Li |
| Latent Class Clustering of Random Coefficient Estimates Obtained from a Multilevel Analysis | Jay Magidson Jeroen Vermunt |
Session 8B: Restructuring Basic Statistical Curricula: Mixing Older Analytic Methods with Modern Software Tools in Psychological Research
Room TBA
| Paper | Authors |
| Restructuring Basic Statistical Curricula: Mixing Older Analytic Methods with Modern Software Tools in Psychological Research | Emil Coman James Jaccard Sabrina Uva Ana-Maria Cazan |
Session 8C: Advancing Research on Methodology: A Panel Discussion on the Creation of a Minority-Centered Methodological conference, InclusiMetrics
Room TBA
| Paper | Authors |
| Advancing Research on Methodology: A Panel Discussion on the Creation of a Minority-Centered Methodological Conference, InclusiMetrics | Marcus Harris Zachary Collier |
Session 8D: Innovations in Structural Equation Modeling
Room TBA
| Symposium | Authors |
| Introducing the Deleted One Covariance Residual Measure to the Structural Equation Modeling | Fathima Jaffari Jennifer Koran |
| Ruling Out Latent Time Varying Confounders in Two-Variable Multi-wave Studies | David Kenny D. Betsy McCoach |