Structural Equation Modeling: New Developments and Applications
The goal of this meeting is to bring together methodological and substantive researchers who work on or are interested in working on structural equation modeling (SEM).
The meeting will be organized together with the 2022 meeting of the Working Group SEM. Researchers will present about new methodological developments, novel applications, or new software packages. There will be various keynote presentations by leading researchers in the world of SEM (see below). Additionally, we invite researchers to submit abstracts to present their research on SEM.
Abstracts for a presentation should be submitted before January 7, 2022 Please send an e-mail to: firstname.lastname@example.org with the abstract. We will inform you whether your abstract has been accepted before February 1, 2022.
- Prof. Dr. Yves Rosseel (Ghent University): Small sample solutions for SEM
- Prof. Dr. Rogier Kievit (Radboud University): Attack of the Psychometricians II: They’re coming for your brains
- Dr. Suzanne Jak (University of Amsterdam): Current opportunities and challenges in meta-analytic structural equation modeling
- Dr. Daniel Oberski (Utrecht University): SEMs as computation graphs and other useful insights from machine learning.
- Dr. Sara van Erp (Utrecht University): Bayesian regularized SEM: What, why, and how?
Structural Equation Modeling with lavaan: Prof. Dr. Yves Rosseel
Structural equation modeling (SEM) is a general statistical modeling technique to study the relationships among a set of observed variables. It spans a wide range of multivariate methods including path analysis, mediation analysis, confirmatory factor analysis, growth curve modeling, and many more.
The aim of this workshop is twofold. First, we will present a concise overview of the theory of structural equation modeling (SEM), including many special topics (e.g. handling missing data, nonnormal data, categorical data, longitudinal data, and multilevel data). Second, hands-on sessions are included in order to ensure that all participants are able to perform the analyses using SEM software. The software used in this workshop is the open-source R package \`lavaan' (see http://lavaan.org).
Bayesian Structural Equation Modeling: Dr. Sara van Erp
Bayesian SEM is becoming increasingly popular due to various advantages it can offer compared to classical SEM. However, the practical application of Bayesian SEM does require a certain familiarity with Bayesian statistics and knowledge of software packages offering Bayesian SEM. During this workshop, I will introduce Bayesian statistics while focusing on its specific application in the context of SEM. Important practical considerations such as specification of the prior distribution and convergence of the estimation procedure will be discussed. Finally, participants will gain hands-on experience with estimating Bayesian structural equation models using the freely available R package blavaan.
If you have any questions regarding the SEM conference, feel free to contact us via e-mail: email@example.com
Program Structural Equation Modeling: New Developments and Applications
Location: Tilburg University, Simon Building (S8)
Wednesday March 9, 2022 (online only)
- 10:00-13:00: workshop "Structural Equation Modeling with lavaan" (Yves Rosseel; online)
- 13:00-14:00: lunch break
- 14:00-17:00: workshop "Bayesian Structural Equation Modeling" (Sara van Erp; online)
Thursday March 10, 2022
- 09:00-09:25: walk-in/coffee
- 09:25-09:30: welcome
- 09.30-10.30 Keynote Rogier Kievit:
Attach of the Psychometricians 2: They're coming for your brains (live)
- 10:30-10:45: break
- 10:45-11:15: Dandan Tang:
Bayesian evaluation of approximate measurement invariance (online)
- 11:15-11:45: Andrej Srakar:
Adaptive wavelet estimation of a latent variable model (online)
- 11:45-13:00: lunch break
- 13:00-14:00: Keynote Yves Rosseel:
Small sample solutions for SEM (live)
- 14:00-14:15: break
- 14:15-14:45: Rebecca Kuiper
What's wrong with the null hypothesis? New methods for informative hypothesis testing (live)
- 14:45 - 15:15: Terrence D. Jorgensen:
Pooled score tests for SEM with mulitply imputed data (live)
- 15:15-15:30: break
- 15:30-16:00: Sacha Epskamp:
Introducing psychonetrics, an R package for structural equation modelling and network psychometrics (live)
- 16:00-16:30: Kim De Roover
Mixture multigroup factor analysis for unraveling measurement non-invariance across many groups (live)
- 16:30-20:00: drinks and dinner @ Boerke Mutsaers
Friday March 11, 2022
- 09:00-09:30: walk-in/coffee
- 09:30-10:30: Keynote Suzanne Jak:
Current opportunities and challenges in meta-analytic structural equation modeling (live)
- 10:30-10:45: break
- 10:45-11:15: Hannelies de Jonge:
Using meta-analytic structural equation modeling to synthesize data of randomized controlled trials (live)
- 11:15-11:45: Xi Yu:
A new approach for modeling aggregate constructs (live)
- 11.45-13.00: lunch break
- 13.00-14.00: Keynote Daniel Oberski:
SEMs as computation graphs and other useful insights from machine learning (online)
- 14:00-14:30: Wen Wei Loh:
Data-driven covariate selection for confounding adjustment by focusing on the stability of the effect estimator (online)
- 14.30-14:45: break
- 14:45-15:45: Keynote Sara van Erp:
Bayesian regularized SEM: What, why, and how? (live)
- 15:45-16:00: closing