QRM Conference 2026
The School of Quantitative Research Methods in Education is pleased to invite educational researchers, PhD students, and senior researchers with an interest in quantitative research methods to our annual conference that takes place on June 15-16.
Call for submissions
With the purpose of sharing knowledge and making connections, QRM encourages doctoral students and researchers to present their ongoing research. We invite proposals for individual papers and posters at the QRM conference. Please note that the conference will be conducted exclusively in English. Participation in our conference, including registration and submissions, is free of charge.
The submissions may address a wide range of educational research questions using quantitative methods relevant to, for example, national or international large-scale assessments, as well as issues of social recruitment, segregation, and inequality across the educational system. We also welcome submissions that target methodological considerations and challenges in quantitative research. Submit your poster abstract via the poster submission form and/or your paper abstract via the paper submission form no later than April 12.
Registration
Places are limited, and priority will be given to those who have participated in QRM courses or have registered to become member of the QRM network.
The conference dinner, free of charge, takes place at OGBG Bar & Restaurang. A vegetarian buffet will be served to those who wish to join and indicate it when registering.
Register no later than May 29 via the registration form. Conference dinner registration is only available to those who sign up by May 15.
Keynote speaker
Keynote: Unlocking potential - How the combination of survey and administrative data can inform research in education
As education systems grapple with increasingly complex societal and developmental challenges, researchers need data infrastructures that allow them to understand these issues in deeper and more nuanced ways. In Norway, the possibility to link national administrative data with large-scale survey and genetic data offers exactly such a powerful infrastructure. Drawing on ongoing work within this major linkage project, the talk will describe data sources and access and illustrate how combining administrative records with longitudinal family and health data opens new possibilities for educational research, particularly in understanding learning, development, and inequality. Current limitations will also be discussed, as well as the substantial future potential as additional administrative data and possible linkage to ILSAs become available.
Professor Astrid M. J. Sandsør uses register data in combination with quasi-experimental methods to uncover causal effects of educational policies, with a particular focus on educational inequality. She holds a PhD in Economics and is professor at the Centre of Excellence CREATE - Centre for Research on Equality in Education and at the Department of Special Needs Education, University of Oslo. She has been a member of a government-appointed public commission examining the national admission system to higher education (Norwegian Official Report NOU 2022: 17) and the expert group on how childcare, schools and after school care can contribute to reducing social inequalities (2023-2024). She is an IZA fellow and a CESifo affiliate and was a member of the Young Academy of Norway (2021-2025).
You can find her on LinkedIn https://www.linkedin.com/in/astrid-sandsor/
UiO profile page: https://www.uv.uio.no/isp/english/people/aca/amsandso/index.html
Personal website: https://sites.google.com/site/astridsandsor/home
Workshops
The conference will offer the following workshops
Workshop A
Title: An introduction to latent class analysis
Workshop leader: Kajsa Yang Hansen Department of Education and Special Education, Gothenburg University, Sweden
kajsa.yang-hansen@ped.gu.se
This workshop offers a practical introduction to latent class analysis (LCA). LCA is an individual-centered, model-based method that classifies cases into unobserved, homogeneous groups based on the conditional probabilities of a set of observed categorical variables, given the latent classes. This approach makes LCA particularly valuable for examining individual differences in domains such as learning strategies, study habits, or behavioral patterns. The primary objectives of LCA are to determine the optimal number of latent classes, estimate the proportions of cases in each latent class, and identify their unique response patterns. Moreover, class membership can be used as a predictor or an outcome in relation to other variables, enhancing its analytical potential. This workshop introduces key LCA concepts, outlines detailed procedural steps, and explains decision criteria for model and latent class selection. Examples will be given using available data and the statistical software Mplus and R. Please note that the workshop serves a gentle start of LCA modeling, a preparation for researchers into the more advanced latent variable mixture modeling world.
Targe group: Doctoral candidates and senior researchers in social and behavioral sciences
Prerequisites: basic statistics, regression analysis and basic structural equation modeling technique.
Learning outcomes: After the workshop, participants are expected to gain some understanding of the methods and be able to apply basic LCA/LPA models to their own data. Additionally, they will be equipped to read and critically assess the credibility of scientific articles that utilize these methods.
Workshop B
Title: Using Register Data in Educational Research - with examples in R
Workshop leader: Professor Marie Wiberg
Department of Statistics, Umeå School of Business, Economics and Statistics (USBE), Umeå University, Sweden
In this workshop, we will explore how register-based measures can be applied in educational research. Particular attention will be given to the use of covariates or background variables and to methods for combining them—specifically through the construction of propensity scores. We will illustrate how these scores can be employed in studies using register data. We will use regression and logistic regression with the focus on drawing valid conclusions from register data. Throughout the workshop, we will provide concrete examples using available datasets and demonstrate the implementation in the statistical software R, together with RStudio.
Target group: Doctoral students and senior researchers in the social and behavioral sciences.
Prerequisites: Basic knowledge of statistics, descriptive statistics and basic knowledge of R.
Learning outcomes: After completing the workshop, participants will understand how to incorporate covariates in educational research, and for drawing inferences from register data. Participants will also be equipped to critically evaluate scientific articles that apply covariates in their analyses.
Venue and Accommodation
The conference takes place at Pedagogen, located at the very heart of Gothenburg, within walking distance to the central station and many nearby hotels and tourist attractions.
Conference venue
The address is Pedagogen Hus A, Västra Hamngatan 25, 411 17 Göteborg.
Hotel recommendations
- Elite Plaza Hotel
Link to the hotel's website - Comfort Hotel
Link to the hotel's website