|Dataset Full Name||American Community Survey|
The American Community Survey (ACS) is an annual survey conducted by the U.S. Census Bureau that collects information on a sample drawn from the U.S. institutionalized and non-institutionalized populations and Puerto Rico (Puerto Rico Community Survey – PRCS) The survey covers a broad range of topics including: age, sex, race, family and relationships, income and benefits, health insurance, education, veteran status, disabilities, as well as housing characteristics.
The ACS surveys approximately 3 million addresses in the United States annually, as well as a 2.5 percent sample of the population living in group quarters and 36,000 addresses in Puerto Rico. In 2010, pooled years of the ACS replaced the decennial Census long form. The objective of ACS is to provide federal, state and local governments with up to date information help to plan investments and services.
|Key Terms||Nationally representative, Institutionalized population, Census Bureau, Survey, Local data|
|Sponsoring Agency/Entity||U.S. Census Bureau||Health Conditions/Disability Measures|
|Disability Measures||Visual disability, Hearing disability, Ambulatory disability, Cognitive disability, Self-care disability, Independent living disability, Veterans service connected disability (and rating)||Measures/Outcomes of Interest|
|Topics||Employment, Income, Poverty, Occupation, SSA program participation, Housing & household characteristics, Transportation (commuting), Health insurance||Sample|
|Sample Population||Households, Institutionalized & Non-Institutionalized Group Quarters|
|Sample Size/Notes||Annual Public Use Microdata Sample (PUMS) contains approximately 3 million person records (since 2005)|
|Unit of Observation||Individual & household|
|Geographic Coverage||U.S. (ACS), and Puerto Rico (PRCS)|
|Geographic specificity||U.S. and state levels, some larger counties, Public Use Microdata Areas (PUMAs): 100,000 total population minimum||Data Collection|
|Data Collection Mode||
Multi-modal in the following order:
|Years Collected||2000 - present|
|Data Collection Frequency||Annual||Strengths and Limitations|
|Strengths||Current data, includes institutionalized population (2006 onward). Very high response rate (95.8% in 2015). Can develop estimates at the local level (e.g., county, MSA). ACS PUMS files available as single year as well as 3 and 5 year combined files. The multi-year files provide a larger sample to work with for greater precision.|
|Limitations||Disability questions changed in 2008- complete break from prior years. No specific health conditions. Geographic specificity is limited to Census Bureau defined Public Use Microdata Areas (PUMAs) containing a minimum total population of 100,000, even in multi-year files. Change in sampling in 2005 results in non-comparable data prior to 2005||Data Details|
|Data Access Requirements||Public Use Dataset|
U.S Census Bureau American Factfinder:
|Data Components||Population records Housing unit records (PUMS Data may be downloaded at the national or individual state level)||Selected papers|
Erickson, W. (2012, December). A Guide to Disability Statistics from the American Community Survey (2008 Forward). Cornell University, Ithaca, NY. http://digitalcommons.ilr.cornell.edu/edicollect/1290
ACS Design and Methodology (January 2014):
ACS Questionnaire Archive:
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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).
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Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.
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