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 Effects of Measurement Error in the American Community Survey on Statistical Analysis: An Example using County and Census Tract Mortality Rates.

2019 ◽  
Author(s):  
Corey Sparks ◽  
Lloyd B. Potter
Keyword(s):  
Bayesian Model ◽  
The United States ◽  
Mortality Rates ◽  
Community Survey ◽  
Standard Errors ◽  
American Community Survey ◽  
Regression Analyses ◽  
Census Tracts ◽  
Indicator Data ◽  
Naive Model

The American Community Survey (ACS) summary file data provide rolling 5-year estimates of demographic and socioeconomic indicator data for small geographiesthroughout the United States. These estimates are commonly used as indicators forregression models to measure conditions in communities. The Margins of Error (MOE) inthe ACS estimates for small geographic areas can often be very large, and without takingthem into account, regression analyses using them can be mis-specified, leading to bias inregression coefficients and model standard errors. This paper directly comparesmeasurement error model specifications to naive model specifications for a mortalityoutcome in Texas Census tracts using Bayesian model specializations. The results showthat there is bias in the naive regression model results. We urge users of the ACSsummary file data to be aware of such bias as it can potentially impact interpretation ofmodel results and hypothesis tests.

scholarly journals The Effect of Segregated Cities on Ethnoracial Minority Healthcare System Distrust

2017 ◽  
Author(s):  
Joseph Gibbons
Keyword(s):  
Health Outcomes ◽  
Healthcare System ◽  
Hierarchical Linear Modeling ◽  
Minority Health ◽  
Health Management ◽  
Community Survey ◽  
American Community Survey ◽  
Linear Modeling ◽  
The Public ◽  
Black Neighborhoods

Distrust of the health system is a longstanding issue for ethnoracial minorities, especially for Blacks. Not well understood, however, is the role ethnoracial segregation within a city plays in this distrust. While segregation is typically associated with neighborhood ills, there is evidence that it also can moderate distrust. This study draws on the 2008 wave of the Public Health Management Corporation's Southeastern Pennsylvania Household Health Survey and the 2005-2009 American Community Survey to explore the possibility that segregation effects healthcare system distrust. Using Hierarchical Linear Modeling, we find residence in predominately Black neighborhoods was associated with less distrust in the healthcare system for the Black respondents while residence in mixed neighborhood was associated with more distrust for Black respondents. These findings call for a reevaluation of how healthcare system distrust is understood. Distrust has been connected to poorer health outcomes, playing into wider gaps in ethnoracial minority health outcomes.

Using a GIS and the American Community Survey to Address Community Health Problems

2011 ◽  
pp. 43-56
Author(s):  
J.ane L. McCall ◽  
Amy K. Pasini ◽  
Richard B. Wait
Keyword(s):  
Public Health ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Community Health ◽  
Case Studies ◽  
Geographic Information ◽  
Community Survey ◽  
American Community Survey ◽  
The Public ◽  
Community Data

This chapter describes two case studies that demonstrate how the technology of Geographic Information Systems (GIS) can be combined with community data to address healthcare problems. The purpose is to present a model that can be replicated by other hospitals or those with an interest in promoting the public health.

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.

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