The Effects of Microsuppression on State Education Data Quality

States often turn to a data masking procedure called microsuppression in order to reduce the risk of disclosing student records when sharing data with external researchers. This process removes records deemed to have high risk for disclosure should data be released. However, this process can induce...

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Bibliographic Details
Published in:Journal of research on educational effectiveness 2020-10, Vol.13 (4), p.794-815
Main Authors: Schauer, Jacob M., Kuyper, Arend M., Hedberg, Eric C., Hedges, Larry V.
Format: Article
Language:English
Subjects:
Data disclosure
data privacy
data quality
Data Use
Disclosure
Educational Legislation
Educational Research
FERPA
Parent Rights
Privacy
Scores
SLDS
State Policy
Statistical Bias
Student Records
Student Rights
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Summary:States often turn to a data masking procedure called microsuppression in order to reduce the risk of disclosing student records when sharing data with external researchers. This process removes records deemed to have high risk for disclosure should data be released. However, this process can induce differences between the original data and the data that ultimately gets used in education research. This article assesses the extent to which microsuppression can bias key statistics in state education data and finds that while marginal test score means tend to be preserved in the masked data, conditional means for subgroups can exhibit bias as large as 0.3 standard deviations.
ISSN:1934-5747
1934-5739
DOI:10.1080/19345747.2020.1814465