Causal Inference and COVID: Contrasting Methods for Evaluating Pandemic Impacts Using State Assessments
Link to Resource: Causal Inference and COVID: Contrasting Methods for Evaluating Pandemic Impacts Using State Assessments
Authors: Benjamin Shear, University of Colorado
This paper describes threats to making valid causal inferences about pandemic impacts on student learning based on cross-year comparisons of average test scores. The paper uses Spring 2021 test score data in Colorado to compare three different statistical adjustments that have been used to make inferences about pandemic impacts. Results illustrates how unadjusted cross-year comparisons may be misleading and highlight instances when the statistical adjustments can lead to different conclusions about the relative impacts for different groups of students.
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