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Suppression and Complementary Suppression

The LaunchBoard adheres to the privacy requirements in the Family Educational Rights and Privacy Act (FERPA) of 1974 along with other best practices in order to protect students’ right to privacy. FERPA is a federal law that protects the privacy of student education records and pertains to the release of and access to educational records or any information directly related to a student that are maintained by an educational institution or agency or other party acting on their behalf. The law applies to all schools that receive funds under applicable programs of the US Department of Education.

The California convention for protecting personally identifiable data is that information for groups of less than 10 students may not be reported in aggregated tables. For the LaunchBoard additional practices have been adopted from Federal guidelines as well as from other states such as Texas. This includes complementary suppression. Complementary suppression rules are applied in cases where using simple subtraction from the total could allow viewers to back into the suppressed low value count of a group. Over summer 2020, the Chancellor’s Office convened workgroups that met and approved the FERPA suppression policy applied to the LaunchBoard dashboards.

LaunchBoard Suppression Rules Summary

  • Counts less than 10 and greater than 0 are not shown. For survey data since viewers do not have the information as to which students responded to the survey question, counts less than 3 and greater than 0 are not shown instead.
  • When separate subgroups are masked and added together, they are totaled into a new subgroup called "All Masked Values." If the value of the subgroup is 0, then students in the subgroup denominator are NOT included in the "All Masked Values" category since that subgroup is missing and not masked. The suppressed subgroups that are included in the "All Masked Values" category are listed below the graph.
  • When only one subgroup is masked, complementary suppression is used to prevent users from backing into the masked value of the subgroup with simple subtraction from the overall by masking the smallest unmasked group and adding its value to the "All Masked Values" subgroup.
  • Whenever there are more than one "generated" or "created" subgroups such as "unknown/non-respondent" or "multiple values reported" and either includes a value less than 10, including 0, then the two subgroups are combined and masked together to prevent a possible non-generated subgroup with 10 or greater students from being suppressed.
  • For metrics that are counts, if values for subgroups are identical for complementary suppression, then the metric with the lowest denominator will be suppressed. If values and denominators are the same for subgroups, then an alpha-numeric value (either a label or an ID value) will be used to determine which of the identical subgroups will be masked with consistency. This alpha-numeric value is used to resolve arbitrary ties and produce consistent results across dashboards.
  • For metrics that are not counts (medians, averages, percentages, etc), masking is performed over the n-size of students in the metric - the denominator. Because the denominator is being used as the primary masking value, the same alpha-numeric value as above will be used as the primary, rather than secondary tie-breaker for complimentary suppression of subgroups when denominators are equal.
  • If an overall disaggregation is masked, all subgroups will be masked as well.

How Suppression and Complementary Suppression Work

Unsuppressed: Counts by Race/Ethnicity

EthnicityCount of Students
American Indian/Alaska Native6
Asian88
Black or African American52
Filipino37
Hispanic46
Pacific Islander or Hawaiian Native14
White95
Two or More Races96
Unknown/Non-Respondent50
Multiple Values Reported16
Total500
Table 1

1st Level of Suppression: Suppress counts less than 10 and greater than 0

EthnicityCount of Students This level of suppression is not enough because someone could find the students in the American Indian/Alaska Native category by subtracting the sum of the other ethnicities from the total. Total (500) – All Available Ethnicity Groups (494) = American Indian/Alaska Native (6)
American Indian/Alaska Native*
Asian88
Black or African American52
Filipino37
Hispanic46
Pacific Islander or Hawaiian Native14
White95
Two or More Races96
Unknown/Non-Respondent50
Multiple Values Reported16
Total500
Table 2

Complementary Suppression: When only one subgroup is masked, suppress the subgroup with the next lowest count

EthnicityCount of Students By implementing complementary suppression someone could not use simple mathematics to determine the data for the American Indian/Alaska Native category. Masked values will be grouped together and displayed together in the "All Masked Values" category in the LaunchBoard. In this example, "All Masked Values" would include American Indian/Alaska Native and Pacific Islander or Hawaiian Native.
American Indian/Alaska Native*
Asian88
Black or African American52
Filipino37
Hispanic46
Pacific Islander or Hawaiian Native*
White95
Two or More Races96
Unknown/Non-Respondent50
Multiple Values Reported16
All Masked Values20
Total500
Table 3

Complementary Suppression When Two or More Generated Subgroups Are Present

The example below illustrates how suppression is being implemented on the LaunchBoard when two or more generated subgroups are present. This additional step was implemented to ensure that data for important populations are displayed wherever possible.

Unsuppressed: Counts by Gender

GenderCount of Students
Female25
Male13
Unknown/Non-Respondent5
Multiple Values Reported17
Total60
Table 4

Suppressed: Suppress counts less than 10 and suppress the value of generated subgroups for complementary suppression instead of following the rule above

GenderCount of Students In this instance, the multiple values reported subgroup is masked even though it had a value greater than 10 and was not the next smallest group. This ensures that the Male subgroup is displayed.
Female25
Male13
Unknown/Non-Respondent*
Multiple Values Reported*
All Masked Values22
Total60
Table 5

Suppression for Secondary Gender Disaggregation in the Cohort View of Student Success Metrics

In order to meet the legislative requirements of Student Equity Achievement (SEA), a secondary disaggregation on gender was included to the Cohort View of the Student Success Metrics dashboard. Data is displayed in order to determine possible equity gaps for additional subgroups (e.g. female veterans vs male veterans). The Chancellor’s Office made the decision to create a new subcategory labeled "All Other Values" to group together the new non-binary value, created in summer 2019, and the two generated subgroups discussed above (multiple values reported and unknown/non-respondent) regardless of the size of the counts for two main reasons: legibility of the display of further gender disaggregations on one graph and low "n" sizes for those subgroups resulting in suppressed data and the inability of colleges to determine equity gaps for those subgroups to include in SEA plans.

Unsuppressed Primary Disaggregation: Counts by First Generation Status - Prior to Secondary Gender Disaggregation

First GenerationCount of Students
First Generation80
Not First Generation75
Unknown/Unreported5
Total160
Table 6

Suppressed: Suppresses counts less than 10, and when only one subgroup is masked, suppress the subgroup with the next lowest count

First GenerationCount of Students Unknown/Unreported is masked since <10. The next highest subgroup, Not First Generation, is also masked for complimentary suppression rules.
First Generation80
Not First Generation*
Unknown/Unreported*
All Masked Values80
Total160
Table 7

Unsuppressed Secondary Disaggregation: Counts by First Generation Status further disaggregated by Gender

GenderFirst GenerationCount of Students
FemaleFirst Generation45
FemaleNot First Generation30
FemaleUnknown/Unreported1
MaleFirst Generation30
MaleNot First Generation35
MaleUnknown/Unreported3
All Other ValuesFirst Generation5
All Other ValuesNot First Generation10
All Other ValuesUnknown/Unreported1
Total160
Table 8

Second Level Suppression: Within the secondary gender disaggregation subgroups, implement the standard suppression and complementary suppression logic for the primary disaggregation. Then sum together all masked values for display within the "All Other Values" category as "All Masked Values."

GenderFirst GenerationCount of Students Female Not First Generation is masked due to complementary suppression with Female Unknown/Unreported. Same case with Male First Generation and Unknown/Unreported. All Other Values First Generation and Unknown/Unreported are masked because values are <10. All masked subgroups are summed together and reported as All Masked Values in the All Other Values subgroup.
FemaleFirst Generation45
FemaleNot First Generation*
FemaleUnknown/Unreported*
MaleFirst Generation*
MaleNot First Generation35
MaleUnknown/Unreported*
All Other ValuesFirst Generation*
All Other ValuesNot First Generation10
All Other ValuesUnknown/Unreported*
All Other ValuesAll Masked Values80
Total160
Table 9