By the Numbers: Part Two

• Welcome
• By The Numbers – Part II
• Questions and Answers
• On The Horizon
Overview
2

3
• Alicia VanOrman, PhD
– Population Reference Bureau
• Today we will explore technical
questions related to data
disaggregation in support of evidence-
informed advocacy work
• For more info: avanorman@prb.org
Our Technical Assistance Partner

POPULATION REFERENCE BUREAU | www.prb.org
By the Numbers Part II
Disaggregating Data by
Race and Ethnicity
Alicia VanOrman, Research Associate
October 6, 2016

© 2016 Population Reference Bureau. All rights reserved. www.prb.org
Today’s presentation
Methodological challenges
 Classification schemes
 Dealing with small numbers
Accessing data

Percent minority* by age, 2015-2050
38
40
53
48 50
61
38
41
55
22
24
40
0
10
20
30
40
50
60
70
2015 2020 2050
Total
Ages 0-17
Ages 18-39
Ages 65+
*Includes those who are not non-Hispanic white (alone).
Source: Population Reference Bureau analysis of 2014 U.S. Census Bureau Population Projections.

What are you measuring?
Racial categories are defined by
social, economic, political
institutions
 Categories change over time,
depends on social context
Ethnicity is separate from race
 Refers to ancestry or heritage
 Federal statistical system only
collects data on Hispanic/Non-
Hispanic ethnicity

Guidelines for collecting data
OMB guidelines adopted in 1997
 Two question format
 Option to select multiple racial designations
 Department of education fully implemented in 2010
Minimum
 American Indian or Alaska Native
 Asian
 Black or African American
 Native Hawaiian or Other Pacific Islander
 White
 Hispanic or Latino (asked in a separate question)

Guidelines for collecting data
Variation across data sources
 Mutually exclusive groups (e.g., non-Hispanic Black or African
American)
 Combining categories (e.g., National Survey of Children’s Health)
Coverage
 Did all local entities report data in the same way (e.g., police
jurisdictions)?

Working with small numbers
Maintaining confidentiality
 Smaller populations = easier to identify an individual
Providing reliable estimates
 Smaller populations = more sampling variability
Multiple options for assessing and dealing with these
challenges

Are you working with confidential data?
 Data provider may have prevented disclosure already
 E.g., ACS tables, birth and death data through CDC Wonder
 Check for guidelines from the data source
 E.g., numerator less than 3
Assess the numerator and denominator
 Compared to data source guidelines
 General guidelines
 Numerator/event data: 0 or >2
 Denominator/population: >300, 100-300 use caution, <100 use extreme caution
Avoiding disclosure

Assessing reliability
Reliability measure Reliability estimate
Standard error
• Estimated deviation from actual population value .6
Margins of error
• Maximum amount of difference between sample
estimate and actual population value
±1 percentage point
(90% confidence level)
Confidence interval
• Range of values that describe the uncertainty around an
estimate
19.9%-21.8%
(90% confidence interval)
Coefficient of variation
• Relative amount of sampling error
• 𝐶𝑉 =
𝑆𝐸
෠𝑋
∗ 100
3%
20.9% of children in Nevada are living in poverty.
Source: Population Reference Bureau analysis of 2015 1-year ACS data, Table B17001

No hard and fast rules; depends on the application
Confidence intervals for percents
 Less than 10 percentage points
Coefficients of variation
 Smaller CVs (<15%) indicate greater reliability; larger CVs
(>30%) indicate unreliable data
 Don’t use when proportion is close to zero
What is an acceptable amount of error?

Options for presenting data
Reliable estimates
 Present the estimate with the reliability measure
Borderline reliable estimates
 Present the estimate with note to use caution
 Aggregate to increase sample size
Unreliable estimates and/or disclosure risk
 Aggregate to increase sample size
Suppress estimates

What the federal government does
National Center for Health Statistics
 Less than 10 events: suppress count and rate
 Less than 20 events: suppress rate
National Health Interview Survey, other health surveys
 Relative Standard Error >30%
U.S. Census Bureau
 Population and geography thresholds (e.g., 65,000 for 1-year ACS estimates)
 Significance tests (e.g., >half of estimates are not significantly different from 0)
 Relative standard errors (median CV>61%)

What KIDS COUNT does
Guidelines provided by data source
Aggregate data across years
 ACS: 3 and 4 year olds not enrolled in school
Data suppression
 ACS
 confidence intervals greater than 10 percentage points
 Less than 3 cases

Aggregating data
Combine multiple years of data
 5-year ACS data
 Custom multiyear estimations: ACS Data User Group Webinar
Expand the geographic area
 Combine smaller levels of geography into a larger group (e.g.,
combine counties to create county groups)

Poverty rates for Latino children,
Selected years and geographies
0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0
United States 2014
United States 2010-2014
Maryland 2014
Maryland 2010-2014
Baltimore 2014
Baltimore 2010-2014
Source: U.S. Census Bureau, American Community Survey.

Aggregating by collapsing categories
Asian, Pacific Islander, American Indian/Alaska Native,
and two or more races
17.5% ± 1.8
Asian and Pacific Islander and
American Indian/Alaska Native
12.0% ± 2.2
Asian and Pacific Islander
12.0% ± 2.4
Asian
11.8% ± 2.4
Native Hawaiian
or other Pacific
Islander
18.8% ± 9.6
American
Indian/Alaska
Native
12.0% ± 6.1
Two or more
races
20.5% ± 2.5
Black or African
American
35.6% ± 1.3
Non-Hispanic
White
14.5% ± .7
Hispanic
28.2% ± 1.1
Source: Population Reference Bureau analysis of 2015 1-year ACS data, Table C17001 series
Percent of children in poverty by race and ethnicity, Florida, 2015

Aggregating data
Technical considerations
 Microdata is more flexible
 Use aggregate numerators and aggregate denominators for rates
෢𝑃𝑦1 + ෢𝑃𝑦2 + ෢𝑃𝑦3
3
≠
෢𝑁𝑦1 + ෢𝑁𝑦2 + ෢𝑁𝑦3
෢𝐷 𝑦1 + ෢𝐷 𝑦2 + ෢𝐷 𝑦3
 Standard errors/margins of error
 ACS Accuracy of Data Documentation
 ACS Data User Group Webinar

Aggregating data
Conceptual considerations
 Tradeoffs between data that is less current, has less geographic
detail or less sub-group specificity
 Best option will vary based on goals and data availability
 Some data is better than no data

Accessing data
ACS collects detailed race
and ethnicity data
 Alone: a single race
 Alone or in combination: a
single race and those who
designated multiple races
 White alone: does not
consider the question
about Hispanic origin
 White, non-Hispanic or
Latino: White only and not
Hispanic

Accessing data by race and ethnicity:
American Community Survey
Basic counts for total population by detailed racial and
ethnic groups (alone)
(there are also tables by alone and in combination)
1-year ACS Table 5-year ACS Table
Asian B02015 B02006
Native Hawaiian and other Pacific
Islander
B02016 B02007
American Indian or Alaska Native B02014 B02005
Hispanic or Latino B03001 B03001

Social and economic characteristics by detailed race
and ethnicity
 Very little data available
 Selected Population Profiles: 1-year data only
 Advanced Search -> Race and Ethnic Groups -> Detailed groups
-> All available races

American FactFinder
detailed and subject tables
by race and ethnicity
Identified with a letter after
the table number
 B17001B: Poverty Status, Black or
African American Alone
Categories available:
 White
 Black or African American
 American Indian and Alaska Native
 Asian
 Native Hawaiian and other Pacific Islander
 Other races
 Two or more races
 White, not Hispanic or Latino
 Hispanic or Latino

Table identifier on
American FactFinder
Category on KIDS COUNT Data Center
C American Indian
D + E Asian and Pacific Islander
B Black or African American
I Hispanic or Latino
H Non-Hispanic White
G Two or more races
Add tables together
using aggregation
methods previously
discussed

List of all tables disaggregated by race and ethnicity
 Advanced Search -> Race and Ethnic Groups -> Basic Groups
-> Select group of interest

Accessing Data by Race and Ethnicity:

Counts for selected tribal groupings
 B02014 (AIAN alone): 1-year data, US and very few states
 B02017 (AIAN alone or in combination): 1-year data, few states
 B02005 (AIAN alone): 5-year data, all states
Social and economic characteristics by tribe
 Selected Population Profiles, 1-year data only, US and few states
 By state: 2006-2010 Data Profiles 2, 3, and 4
American Indian Area/Alaska Native Area/Native
Hawaiian Home lands
 5-year data: 693 areas available
 1-year data: 12 areas available

Public Use Micro Sample Data (PUMS)
 Flexible, custom tabulations
 Geographic data is limited
 Need statistical software (e.g., SAS)
 Calculating margins of error can be technical
 See PUMS Accuracy of Data document
 Download data files on AFF or Census website

PUMS via IPUMS
 Custom tabulations, 1-year and 5-
year ACS data
 Recode and create variables
 Some effort to make race and ethnicity
categories match those in KIDS COUNT
 Produces standard errors
 Download microdata
 Need statistical software (e.g., SAS)
 Multiple years of data at once, data are
harmonized

CDC Wonder
 Births
 Deaths
 Data by state and by
county
 Publically available birth data
limited to counties larger than
100,000
 Suppressions rules have
already been applied
Vital Statistics

Civil Rights Data Collection
 Data pre-tabulated by state
 Data available at school district
and school levels
 Use the data analysis tools to compare
multiple schools or districts
 Can request a data file to use with
statistical software to analysis all
districts or schools at once
Education-related data

National Center for Education
Statistics and Ed Data
Express
 State-level data
Education-related data

Looking ahead
Combining two-question format into one question
Middle Eastern or North African (MENA) category
2020 Census & 2019 ACS
 2015 National Content Test
Office of Management and Budget
 Seeking review and comments on possible changes
 Federalregister.gov for more information

For more information
Alicia VanOrman
avanorman@prb.org
202-939-5474

42
• Availability of recorded content for future
reference
• The discussion continues at the KIDS COUNT
Institute and through future webinars co-hosted
with our state partners.
On The Horizon

Developing solutions to build a brighter future for children, families and communities
www.aecf.org

By the Numbers: Part Two

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