PISA-D Data
All statistics were computed using sampling weights; standard errors based on balanced repeated replication weights were used for statistical significance and/or confidence intervals.
Analyses based on achievement test results (plausible values) were based on Rubin’s rule for multiply imputed variables.
The OECD average and PISA-D average corresponded to the arithmetic mean of the respective country estimates in each case.
The PISA data analysis manual provides SAS and SPSS codes for analyzing PISA microdata.
User-written software is also available in Stata (repest, pisatools) and R (intsvy).
Basic statistics can be computed with the PISA Data Explorer.
In-school
- Student questionnaire data file
- School questionnaire data file
- Teacher questionnaire data file
- Cognitive item data file
Out-of-school
- Individual respondent, parent/guardian, interviewer household observation questionnaire data files
- Cognitive item data file
- Questionnaire timing data file
Most items are kept confidential for re-use in future PISA cycles in order to measure trends. A minority of items are released after each cycle to illustrate new frameworks and provide samples of tasks at different levels of proficiency.