The OECD Programme for International Student Assessment (PISA) surveys collected data on students’ performance in reading, mathematics and science, as well as contextual information on students’ background, home characteristics and school factors which could influence performance. This publication includes detailed information on how to analyse the PISA data, enabling researchers to both reproduce the initial results and to undertake further analyses. In addition to the inclusion of the necessary techniques, the manual also includes a detailed account of the PISA 2006 database. It also includes worked examples providing full syntax in SAS®.Click to Access:
- Publication Date :
- 31 Mar 2009
- DOI :
Multilevel AnalysesClick to Access:
- Pages :
- DOI :
Over the last 20 years, education survey data have been increasingly analysed with multilevel models. Indeed, since simple linear regression models without taking into account the potential effects that may arise from the way in which students are assigned to schools or to classes within schools, they may provide an incomplete or misleading representation of efficiency in education systems. In some countries, for instance, the socioeconomic background of a student may partly determine the type of school that he or she attends and there may be little variation in the socio-economic background of students within each school. In other countries or systems, schools may draw on students from a wide range of socio-economic backgrounds, but within the school, the socio-economic background of the student impacts the type of class he or she is allocated to and, as a result, the within-school variance is affected. A linear regression model that does not take into account the hierarchical structure of the data will thus not differentiate between these two systems.