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The OECD’s Programme for International Student Assessment (PISA) has become one of the key studies for evidence-based education policymaking across the globe. PISA has however received a lot of methodological criticism, including how the test scores are created. The aim of this paper is to investigate the so-called ‘conditioning model’, where background variables are used to derive student achievement scores, and the impact it has upon the PISA results. This includes varying the background variables used within the conditioning model and analysing its impact upon countries relatively positions in the PISA rankings. Our key finding is that the exact specification of the conditioning model matters; cross-country comparisons of PISA scores can change depending upon the statistical methodology used.

Conditioning: how background variables can influence PISA scores