Researcher Guide on Interpreting Impacts


IES released a guide to help researchers avoid common misinterpretations of statistical significance and report study impacts that are more actionable for end users. Improving the quality and relevance of education studies is IES Director Mark Schneider’s central goal for the Standards for Excellence in Education (SEER).

The guide introduces BASIE (Bayesian Interpretation of Estimates), an alternative framework to null hypothesis significance testing, and walks researchers through the key steps of applying BASIE:

  • Select prior evidence based on the distribution of intervention effects from existing impact studies (e.g., IES’ What Works Clearinghouse database).
  • Report traditional (based only on study data) and shrunken (based on both study data and prior evidence) impact estimates.
  • Interpret impact estimates using Bayesian posterior probabilities (or credible intervals).
  • Examine the sensitivity of shrunken impact estimates and posterior probabilities to what prior evidence is used.

The guide includes “express stops” and a simple Excel tool so that researchers can quickly start using BASIE. Detailed “local stops,” technical appendices, and programming code are also provided for evaluation methodologists.

View the guide by clicking here.

This guide is one of a series that helps researchers implement SEER. Guides on generalizability and sharing study data were recently released, and a guide on implementation research is in development and will be announced on

The Institute of Education Sciences, a part of the U.S. Department of Education, is the nation's leading source for rigorous, independent education research, evaluation, statistics, and assessment.

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