Select a school by filtering
Find a school using the state, school sector and school type filters, or enter the first few characters of its name in the search box. You can also use the filters and search box together. Then select the school from the results..
Notes and caveats
- The model used student-level logistic regression to estimate each student’s probability of achieving Strong or Exceeding. The predictors were consistent with those used in the current similar-students model for school average scores.
P(Strong or exceeding) = SEA + SchoolSEA + ATSI + MATSI + PERATSI + ARIA
where
• SEA = student-level index of socio-educational advantage
• SchoolSEA = average student-level socio-educational advantage
• ATSI = Indicator of Aboriginal and Torres Strait Islander status
• MATSI = Indicator of missing Aboriginal and Torres Strait Islander status
• PERATSI = percentage of Aboriginal and Torres Strait Islander students
• ARIA = remoteness classification
- Predicted school-level percentages are calibrated to the corresponding jurisdiction-level result. This is particularly important in the Australian Capital Territory and Northern Territory, where the aggregate predicted percentage may otherwise overstate or understate the actual jurisdiction-level percentage.
- Each school’s result is classified according to the difference between its observed and predicted percentages, expressed relative to the estimated standard error of the school result. The standard error is calculated using a delete-one-student jackknife, under which the estimate is recalculated once for each student, with that student omitted from the calculation.