1 Using the IDB Analyzer V Andrés Sandoval-Hernández – IEA DPC Workshop on using PISA, PIAAC, TIMSS & PIRLS, TALIS datasets Ispra, Italy- June 24-27, 2014 Note: These slides were prepared as part of the IEA training portfolio with the collaboration of IEA staff and resource persons.
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Using the IDB Analyzer V - European Commission Using the IDB Analyzer V Andrés Sandoval-Hernández – IEA DPC Workshop on using PISA, PIAAC, TIMSS & PIRLS, TALIS datasets Ispra,
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1
Using the IDB Analyzer V
Andrés Sandoval-Hernández – IEA DPC
Workshop on using PISA, PIAAC, TIMSS & PIRLS, TALIS datasets
Ispra, Italy- June 24-27, 2014
Note: These slides were prepared as part of the IEA training portfolio with the collaboration of IEA staff and resource persons.
2
Table of contents
• Evaluating statistical significance of mean differences with TIMSS
• Evaluating statistical significance of mean differences between countries with PISA
3
Mean Differences (TIMSS)
Is there a significant difference in mathematics
achievement for students from schools with
different emphasis on academic success?
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What Do we Need to Do?
• Merge the data set for TIMSS 2011 by choosing the school and student background questionnaire and the selected countries
In the NETHERLANDS, there are significant differences between students coming from schools with high and medium emphasis on academic success in comparison with schools with very high emphasis on academic success
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Table of contents
• Evaluating statistical significance of mean differences with TIMSS
• Evaluating statistical significance of mean differences between countries with PISA
9
Mean Comparison between countries (PISA)
Is there a significant difference in the average
sense of belonging to school across countries?
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What Do we Need to Do?
• Start the IDB Analyzer Analysis module using PISA 2012 merged data
• Countries have been merged in the data file:
– Austria
– Denmark
– Netherlands
– Slovak Republic
– Spain
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Analysis: Mean Comparison between Countries (PISA)
•Analysis File: C:\EU_Workshop\Work\PISA_Merged.sav •Analysis Type: PISA Age 15 (Using Teacher Weights) •Statistic Type: Percentages and Means •Grouping Variable: CNT •Analysis Variable: BELONG •Weighting variable: W_FSTUWT