| Title |
Measuring Residential Segregation With the ACS: How the Margin of Error Affects the Dissimilarity Index
|
|---|---|
| Published in |
Demography, January 2017
|
| DOI | 10.1007/s13524-016-0545-z |
| Pubmed ID | |
| Authors |
Jeffrey Napierala, Nancy Denton |
| Abstract |
The American Community Survey (ACS) provides valuable, timely population estimates but with increased levels of sampling error. Although the margin of error is included with aggregate estimates, it has not been incorporated into segregation indexes. With the increasing levels of diversity in small and large places throughout the United States comes a need to track accurately and study changes in racial and ethnic segregation between censuses. The 2005-2009 ACS is used to calculate three dissimilarity indexes (D) for all core-based statistical areas (CBSAs) in the United States. We introduce a simulation method for computing segregation indexes and examine them with particular regard to the size of the CBSAs. Additionally, a subset of CBSAs is used to explore how ACS indexes differ from those computed using the 2000 and 2010 censuses. Findings suggest that the precision and accuracy of D from the ACS is influenced by a number of factors, including the number of tracts and minority population size. For smaller areas, point estimates systematically overstate actual levels of segregation, and large confidence intervals lead to limited statistical power. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Unknown | 79 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 27 | 34% |
| Student > Master | 10 | 13% |
| Researcher | 9 | 11% |
| Professor | 5 | 6% |
| Student > Bachelor | 5 | 6% |
| Other | 13 | 16% |
| Unknown | 11 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 43 | 54% |
| Economics, Econometrics and Finance | 7 | 9% |
| Nursing and Health Professions | 4 | 5% |
| Arts and Humanities | 2 | 3% |
| Medicine and Dentistry | 2 | 3% |
| Other | 5 | 6% |
| Unknown | 17 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 September 2023.
All research outputs
#7,640,242
of 24,549,201 outputs
Outputs from Demography
#1,315
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Outputs of similar age
#134,823
of 426,312 outputs
Outputs of similar age from Demography
#20
of 23 outputs
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