| Summary: | This paper is based on Portuguese data from PISA-2009, and it focuses on the measurement of student achievement in mathematics and on the determinants of this achievement both at the student and at the school levels. Data on about 3900 Portuguese students and 194 schools who participated in PISA-2009 were used to accomplish our objectives. Given the hierarchical structure of data, the models adopted for statistical analysis were multilevel models, which can take into account data variability within and among the hierarchical levels. Specifically we were interested in understanding whether the impact of students' variables were similar for students with diferent levels of achievement. As a result, we used a multilevel quantile regression model to analyse the determinants of students' success, where the potential determinants are student and school variables. Our study provides evidence that a stable relation with achievement is expected for some variables (e.g. gender, repetition, or socio economic back- ground), while other variables show varying impacts depending on the students location on the rank of achievement in maths (e.g. immigrant status of students, or some study strategies like control strategies). In spite of schools having a significant impact on students' achievement (without considering any explanatory factors, 30% of the variability found in students' test scores can be explained by the school attended), we found that most school-level variables (except location) were not significant in explaining the school effect.
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