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Hans Bay, University of Copenhagen, DenmarkAbstract
This paper presents a baseline statistical model for analysing student performance using PISA 2022 data from Denmark. The model draws on student-level background variables, including gender, immigrant background, and socioeconomic status (ESCS), to explain variation in mathematics achievement. Descriptive results show systematic differences across groups, with higher scores observed among boys and students without an immigrant background. A multilevel regression framework is applied to estimate the contribution of individual and school-level factors. The inclusion of school-level socioeconomic composition further improves model fit. In an extended version of the model, the mathematics anxiety index (ANXMAT) is incorporated, leading to a substantial increase in explanatory power. Although the results demonstrate strong statistical associations, they do not imply causal relationships. The paper illustrates a parsimonious modelling strategy suitable as a baseline for comparative analyses of PISA data.
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Conference: WCE2026Stream: Educational Research
This paper is part of the WCE2026 Conference Proceedings (View)
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To cite this article:
Bay H. (2026) A Baseline Statistical Model for Analyzing PISA Data in Denmark ISSN: 2760-7259 The Washington DC Conference on Education 2026: Official Conference Proceedings (pp. 187-194) https://doi.org/10.22492/issn.2760-7259.2026.17
To link to this article: https://doi.org/10.22492/issn.2760-7259.2026.17
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