scholarly journals Public-Use vs. Restricted-Use: An Analysis Using the American Community Survey

2017 ◽  
Author(s):  
Satkartar K. Kinney ◽  
Alan Karr
Keyword(s):  
Community Survey ◽  
American Community Survey ◽  
Restricted Use

scholarly journals Public-Use vs. Restricted-Use: An Analysis Using the American Community Survey

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Saki Kinney ◽  
Alan F Karr
Keyword(s):  
Data Center ◽  
Community Survey ◽  
Standard Errors ◽  
American Community Survey ◽  
Statistical Research ◽  
The Public ◽  
Advantages And Disadvantages ◽  
Data Source ◽  
Statistical Agencies ◽  
Restricted Use

Statistical agencies frequently publish microdata that have been altered to protect condentiality. Such data retain utility for many types of broad analyses but can yield biased or insufficiently precise results in others. Research access to de-identied versions of the restricted-use data with little or no alteration is often possible, albeit costly and time-consuming. We investigate the advantages and disadvantages of public-use and restricted-use data from the American Community Survey (ACS) in constructing a wage index. The public-use data used were Public Use Microdata Samples, while the restricted-use data were accessed via a Federal Statistical Research Data Center. We discuss the advantages and disadvantages of each data source and compare estimated CWIs and standard errors at the state and labor market levels. We find the results from the publicly available data are generally good relative to the restricted-use data, with greater similarity for larger areas and less similarity for smaller areas. Standard errors are higher in the public-used data but may still be underestimated.

scholarly journals The Effect of Data Swapping on Analyses of American Community Survey Data

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Nicolas Kim
Keyword(s):  
Survey Data ◽  
Census Data ◽  
Census Bureau ◽  
Community Survey ◽  
Public Access ◽  
Categorical Variables ◽  
American Community Survey ◽  
Joint Distributions ◽  
Restricted Use ◽  
The U.S

Researchers from a growing range of fields and industries rely on public-access census data. These data are altered by census-taking agencies to minimize the risk of identification; one such disclosure avoidance measure is the data swapping procedure. I study the effects of data swapping on contingency tables using a dummy dataset, public-use American Community Survey (ACS) data, and restricted-use ACS data accessed within the U.S. Census Bureau. These simulations demonstrate that as the rate of swapping is varied, the effect on joint distributions of categorical variables is no longer understandable when the data swapping procedure attempts to target at-risk individuals for swapping using a simple targeting criterion.

Latino Continual Demographic Growth: Implications for Educational Practices and Policy

2020 ◽  
Vol 19 (2) ◽  
pp. 134-148
Author(s):  
Rogelio Sáenz
Keyword(s):  
Undocumented Students ◽  
Population Data ◽  
Community Survey ◽  
Ethnic Composition ◽  
Educational Practices ◽  
American Community Survey ◽  
Undergraduate Enrollment ◽  
Demographic Shifts ◽  
Demographic Growth ◽  
The U.S

Demographic shifts have transformed the racial and ethnic composition of the U.S. undergraduate population. Data from the American Community Survey are used to analyze Latino undergraduate enrollment as well as factors that contribute to the matriculation of undocumented Latino young adults. The article concludes with an overview of the implications of the growth of the Latino population and the experience of undocumented students on educational practices and policies.

Taking a Chance in the Classroom: The American Community Survey

CHANCE ◽  
2013 ◽  
Vol 26 (1) ◽  
pp. 42-46
Author(s):  
Dalene Stangl ◽  
Mine Çetinkaya-Rundel ◽  
Kari Lock Morgan
Keyword(s):  
Community Survey ◽  
American Community Survey

scholarly journals Comparing denominator sources for real-time disease incidence modeling: American Community Survey and WorldPop

2021 ◽  
pp. 100786
Author(s):  
Rachel C. Nethery ◽  
Tamara Rushovich ◽  
Emily Peterson ◽  
Jarvis T. Chen ◽  
Pamela D. Waterman ◽  
...  
Keyword(s):  
Real Time ◽  
Disease Incidence ◽  
Community Survey ◽  
American Community Survey

Measuring the Impact of COVID-19 on Businesses and People: Lessons from the Census Bureau’s Experience

2021 ◽  
Vol 111 ◽  
pp. 312-316
Author(s):  
Catherine Buffington ◽  
Jason Fields ◽  
Lucia Foster
Keyword(s):  
Current Population Survey ◽  
Population Survey ◽  
Census Bureau ◽  
Community Survey ◽  
American Community Survey ◽  
Annual Business ◽  
Data Products ◽  
Business Survey ◽  
The Impact ◽  
Existing Data

We provide an overview of Census Bureau activities to enhance the consistency, timeliness, and relevance of our data products in response to the COVID-19 pandemic. We highlight new data products designed to provide timely and granular information on the pandemic's impact: the Small Business Pulse Survey, weekly Business Formation Statistics, the Household Pulse Survey, and Community Resilience Estimates. We describe pandemic-related content introduced to existing surveys such as the Annual Business Survey and the Current Population Survey. We discuss adaptations to ensure the continuity and consistency of existing data products such as principal economic indicators and the American Community Survey.

ARE HEALTH INSURANCE ITEM ALLOCATIONS IN THE AMERICAN COMMUNITY SURVEY MISSING COMPLETELY AT RANDOM?

2013 ◽  
pp. 1-7
Author(s):  
C. SIORDIA
Keyword(s):  
Health Insurance ◽  
Minority Groups ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Community Survey ◽  
American Community Survey ◽  
Data Sets ◽  
Missing Responses ◽  
Missing Completely At Random ◽  
Racial Ethnic

Background:Item allocation (the assignment of plausible values to missing or illogical responses insurvey studies) is at times necessary in the production of complete data sets. In the American Community Survey(ACS), missing responses to health insurance coverage questions are allocated. Objectives:Because allocationrates may vary as a function of compositional characteristics, this project investigates how seven different healthinsurance coverage items vary in their degree of allocation along basic demographic variables. Methods: Datafrom the ACS 2010 1-year Public Use Microdata Sample file are used in a logistic regression model and tocalculate allocations rates. Results:The findings reveal that: males; people aged 65 and older; those who speakEnglish “very well” or “well”; US citizens; those out-of-poverty; and all racial/ethnic minority groups havehigher odds of experiencing a health insurance item allocation relative to their counterparts. Conclusions: Sincehealth insurance coverage allocations vary by demographic characteristics, further research is needed toinvestigate their mechanisms of missingness and how these may have implications for frailty related research.

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