Two former members of the Psychosystems group – dr. Adela Isvoranu and dr. Sacha Epskamp – are hosting two workshops on network psychometrics at The National University of Singapore (NUS) this summer (2024) from July 29 to August 3. The workshops will cover a broad range of topics in network psychometrics, ranging from introductory concepts and analysis methods to advanced techniques in longitudinal data modeling. Completing both workshops will grant a professional certification from the NUS Faculty of Arts and Social Sciences. For more information and registration, please see the NUS website.
Workshop I: Network Psychometrics: Foundations, Theory, and Cross-sectional Data Analysis (July 29 – July 31)
Course Synopsis
This three-day workshop will focus on both theoretical foundations of network psychometrics and modeling techniques developed from this perspective. It will provide the programming background and skills necessary to carry out independent data analyses, as well as the central concepts in the estimation of psychometric network models. The workshop will consist of plenary lectures (2h), followed by seminar-style computer practicals (1.5h).
Learning Outcomes
After completing this workshop, attendees will be able to:
- Understand the theoretical foundations behind network psychometrics
- Carry out basic programming in R: create a matrix, load and inspect data, computer a variance-covariance matrix, visualize and analyze networks using the qgraph package for R
- Explain the differences between social network analysis and network psychometrics
- Compute network metrics common in the field
- Draw an implied Markov Random Field (MRF) given a certain causal structure
- Be familiar with Gaussian Graphical Models (GGMs), Ising models, and Mixed Graphical Models
- Interpret MRFs in different ways (causal, predictive)
- Estimate unconstrained MRFs from cross-sectional data
- Understand the differences between pruning, model selection, and regularization
- Estimate MRFs using different estimation algorithms and understand which algorithm should be preferred for which setting
- Apply permutation tests to check differences between two groups
- Apply bootstrapping to assess the stability of network model parameters
Dates and Time
- Day 1: 29 July 2024
- Day 2: 30 July 2024
- Day 3: 31 July 2024
Classes will be conducted from 9 am to 5 pm.
About The Trainer
Dr Adela Isvoranu
Assistant Professor, National University of Singapore
Education
Ph.D. (University of Amsterdam, NL; cum laude)
M.Sc. (University of Amsterdam, NL; cum merit)
B.Sc. (Hons.) (University of Leeds, UK)
Dr. Isvoranu is an Assistant Professor at the National University of Singapore, Department of Psychology. Her research focuses on pathways from mental health to mental illness and fuzzy boundaries between psychopathological conditions. Dr. Isvoranu’s PhD work, which she completed cum laude at the University of Amsterdam, argues for complexity-based conceptualizations of psychopathology, focusing on symptoms and their interactions, rather than on syndromes. Dr. Isvoranu works in a multidisciplinary environment, often collaborating with clinical psychologists, practitioners, and methodologists, ultimately aiming to facilitate the development of novel intervention approaches to improve mental health. She is the main author of the textbook “Network Psychometrics with R: A Guide for Behavioral and Social Scientists”. Dr. Isvoranu has recently also been recognized as an APS Rising Star.
Workshop II: Network Psychometrics: Longitudinal Data Modeling (August 1 – August 3)
Course Synopsis
This workshop will focus on longitudinal data modeling in the context of network psychometrics. The material will move the focus from cross-sectional data sets to data sets of one or more people measured repeatedly over time and provide the necessary skills to independently estimate network models from longitudinal data. The workshop will consist of plenary lectures (2h), followed by seminar-style computer practicals (1.5h).
Learning Outcomes
After completing this workshop, attendees will be able to:
- Understand when to use single measurement, panel, and intensive time-series data
- Explain the difference between within-subject effects and between-subject effects
- Estimate vector-autoregression models from longitudinal data
- Critically assess the interpretation from longitudinal data analyses
- Understand the basics of multi-level analysis
- Estimate personalized network models from single subject time-series
- Estimate multi-level network models from time-series data of multiple participants
- Estimate network models from panel data
- Incorporate latent variable and measurement errors in (longitudinal) network models
Dates and Time
- Day 1: 1 August 2024
- Day 2: 2 August 2024
- Day 3: 3 August 2024
Classes will be conducted from 9 am to 5 pm.
About The Trainer
Dr Sacha Epskamp
Associate Professor, National University of Singapore
Education
Ph.D. (University of Amsterdam, NL)
M.Sc. (University of Amsterdam, NL)
B.Sc. (University of Amsterdam, NL)
A/P 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, A/P 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, A/P 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. A/P 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. A/P 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, the junior scientific award of the Complex Systems Society, and the APS Janet Taylor Spence Award.