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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| Veröffentlicht in: | Journal of research on educational effectiveness 2020-10, Vol.13 (4), p.794-815 |
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| container_title | Journal of research on educational effectiveness |
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| creator | Schauer, Jacob M. Kuyper, Arend M. Hedberg, Eric C. Hedges, Larry V. |
| description | 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. |
| doi_str_mv | 10.1080/19345747.2020.1814465 |
| format | Article |
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| ispartof | Journal of research on educational effectiveness, 2020-10, Vol.13 (4), p.794-815 |
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| language | eng |
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| source | Education Source |
| 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 |
| title | The Effects of Microsuppression on State Education Data Quality |
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