Improving power calculations in educational trials

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Durham University

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Improving power calculations in educational trials

Study investigating parameters commonly used for statistical power and sample size calculations

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Statistical power analysis is a crucial aspect of trial design. It helps researchers determine the appropriate sample size needed to detect meaningful effects and ensures that the study has a high probability of detecting real differences if they are present.

 

This report mainly provides estimates for parameters such as correlation coefficients between test scores and intra-cluster correlations (ICC) from Early Years Foundation Stage to Key Stage 4. Estimates are derived through four sets of data: i) all English schools (using the whole National Pupil Database – NPD), ii) a random sample of English schools (also derived from the NPD), iii) schools that have participated in an EEF trial (trials available in the EEF Archive) and iv) the EEF schools with NPD data. 

The EEF encourages evaluators to incorporate these findings when designing forthcoming trials.

Improving Power Calculations in Educational Trials (PDF, 1.4MB)

Funding partners

Education Endowment Foundation logo

Education Endowment Foundation

Education Endowment Foundation website

About this project

Explore the people, research centres and partner organisations behind this project.

Research partners

Durham University

Get in touch

Contact us to discuss facilities, partnerships, doctoral research and more

Email us

Research team

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Sean Demack

Sean Demack
Martin Culliney

Martin Culliney

Martin Culliney