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 Potential Data Sources for a New Study of Social Mobility in the United States

2014 ◽  
Vol 657 (1) ◽  
pp. 208-246
Author(s):  
John Robert Warren
Keyword(s):  
United States ◽  
Social Mobility ◽  
Population Survey ◽  
Data Access ◽  
The United States ◽  
Community Survey ◽  
Data Sources ◽  
American Community Survey ◽  
Costs And Benefits ◽  
Trade Offs

In this article I define the main criteria that ought to be considered in evaluating the costs and benefits of various data resources that might be used for a new study of social and economic mobility in the United States. These criteria include population definition and coverage, sample size, topical coverage, temporal issues, spatial issues, sustainability, financial expense, and privacy and data access. I use these criteria to evaluate the strengths and weakness of several possible data resources for a new study of mobility, including existing smaller-scale surveys, the Current Population Survey, the American Community Survey, linked administrative data, and a new stand-alone survey. No option is perfect, and all involve trade-offs. I conclude by recommending five possible designs that are particularly strong on the criteria listed above.

Analyzing Rates of Seriously Delinquent Mortgages in Asian Census Tracts in the United States

2017 ◽  
Vol 55 (2) ◽  
pp. 616-638 ◽  
Author(s):  
Katrin B. Anacker
Keyword(s):  
Race And Ethnicity ◽  
Weighted Least Squares ◽  
The United States ◽  
Community Survey ◽  
Descriptive Statistics ◽  
Social Differences ◽  
Metropolitan Statistical Areas ◽  
Census Tracts ◽  
Foreclosure Crisis ◽  
The U.S

Although race and ethnicity have been analyzed and discussed in the context of the national foreclosure crisis, there has been little work on neighborhoods in which different Asian subgroups reside, which is surprising given the relatively large demographic, economic, and social differences. Based on NSP 3 data, provided by the U.S. Department of Housing and Urban Development (HUD), and 2005/2009 American Community Survey (ACS) data, provided by the U.S. Bureau of the Census, this article utilizes descriptive statistics and weighted least squares (WLS) regressions to analyze rates of seriously delinquent mortgages for Census tracts in all Metropolitan Statistical Areas (MSAs), differentiating among different Asian subgroups. Findings show that neighborhoods with Hmong, Laotian, and Cambodian households had relatively high rates of seriously delinquent mortgages, whereas neighborhoods with Chinese, Japanese, and Pakistani households had relatively low rates of seriously delinquent mortgages.

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.

The Multilevel Effects of Changes in Disadvantage on Changes in Crime

2021 ◽  
pp. 001112872110475
Author(s):  
Marin R. Wenger
Keyword(s):  
Social Disorganization ◽  
Multilevel Models ◽  
Community Survey ◽  
Social Disorganization Theory ◽  
American Community Survey ◽  
Neighborhood Crime ◽  
Cross Sectional ◽  
Census Tracts ◽  
Multilevel Effects ◽  
Over Time

While social disorganization theory suggests the importance of change, most prior research examining macro-level criminological associations uses cross-sectional data. The current study examines the multilevel relationship between changes in disadvantage and changes in crime over time using four data sources: the National Neighborhood Crime Study, the 2000 U.S. Census, crime-incidents occurring between 2005 and 2009, and the 2005–2009 American Community Survey. Analyzing 6,068 census tracts within 53 large U.S. cities using multilevel models with time nested within tracts nested within cities, I parse out the contribution of changes in tract-level disadvantage from city-level disadvantage to changes in robbery and burglary rates. Results indicate the importance of both static and dynamic associations between disadvantage and crime, at both the neighborhood and city level.

scholarly journals A New Infrastructure for Monitoring Social Mobility in the United States

2014 ◽  
Vol 657 (1) ◽  
pp. 63-82 ◽  
Author(s):  
David B. Grusky ◽  
Timothy M. Smeeding ◽  
C. Matthew Snipp
Keyword(s):  
Social Science ◽  
Labor Markets ◽  
Social Mobility ◽  
Science Inquiry ◽  
The United States ◽  
Great Accuracy ◽  
Community Survey ◽  
Evidence Based ◽  
American Community Survey ◽  
New Infrastructure

The country’s capacity to monitor trends in social mobility has languished since the last major survey on U.S. social mobility was fielded in 1973. It is accordingly difficult to evaluate recent concerns that social mobility may be declining or to develop mobility policy that is adequately informed by evidence. This article presents a new initiative, dubbed the American Opportunity Study (AOS), that would allow the country to monitor social mobility efficiently and with great accuracy. The AOS entails developing the country’s capacity to link records across decennial censuses, the American Community Survey, and administrative sources. If an AOS of this sort were assembled, it would open up new fields of social science inquiry; increase opportunities for evidence-based policy on poverty, mobility, child development, and labor markets; and otherwise constitute a new social science resource with much reach and impact.

scholarly journals Precision of Disability Estimates for Southeast Asians in the American Community Survey 2008-2010 Microdata

2013 ◽  
Vol 2 (1) ◽  
Author(s):  
Carlos Siordia ◽  
Vi Donna Le
Keyword(s):  
Independent Living ◽  
The United States ◽  
Southeast Asian ◽  
Community Survey ◽  
American Community Survey ◽  
Southeast Asians ◽  
Margin Of Error ◽  
The Us ◽  
Long Form ◽  
Hearing Difficulties

Detailed social data about the United States (US) population was collected as part of the US decennial Census up until 2000. Since then, the American Community Survey (ACS) has replaced the long form previously administered in decennial years. The ACS uses a sample rather than the entire US population and therefore, only estimates can be created from the data. This investigation computes disability estimates, standard error, margin of error, and a more comprehensive “range of uncertainty” measure for non-Latino-whites (NLW) and four Southeast Asian groups. Findings reveal that disability estimates for Southeast Asians have a much higher degree of imprecision than for NLW. Within Southeast Asian groups, Vietnamese have the highest level of certainty, followed by the Hmong. Cambodians and Laotians disability estimates contain high levels of uncertainty. Difficulties with self-care and vision contain the highest level of uncertainty relative to ambulatory, cognitive, independent living, and hearing difficulties.

scholarly journals Detecting “real” population changes with American Community Survey data: The implicit assumption of treating between-year differences as “trends”

2014 ◽  
Vol 4 (2) ◽  
pp. 494 ◽  
Author(s):  
Carlos Siordia
Keyword(s):  
Population Change ◽  
The United States ◽  
Community Survey ◽  
Population Characteristics ◽  
American Community Survey ◽  
Implicit Assumption ◽  
Point Estimates ◽  
Real Population ◽  
The Us ◽  
Real Change

<p><strong>Abstract</strong></p><p><strong>BACKGROUND:  </strong>The American Community Survey (ACS) in the United States (US) collects detailed demographic information on the US population. Pressures to use year-to-year population estimates to analyze “trends” (i.e., between-year differences on the characteristics of interest) have motivated the need to explore how single- or multi-year estimates can be used to investigate changes in US population over time. <strong>OBJECTIVE: </strong>The specific aim of this manuscript is to provide empirical evidence that between-year differences in population characteristics have difference levels of uncertainty around point-estimates. <strong>METHODS:</strong> Six ACS Public Use Microdata Sample (PUMS) single year files from 2005 through 2010 are used to empirically show the heterogeneity of uncertainty in “between-year differences” on level of education, for a birth cohort born between 1960 and 1970 of non-Latino-whites and Mexican Latinos/as. <strong>RESULTS: </strong>The data show the precision of the education estimate decreases as the specificity of the population increases. For example, Mexican’s 99% confidence intervals have wider and more time-varying bandwidths than non-Latino-whites. <strong>CONCLUSIONS: </strong>Inferring meaningful population change requires the challengeable assumption that between-year differences are not the product of data artifacts. Harvesting reputable ACS data demands further research before between-year differences can be treated as “real change.”    </p><p> </p>

scholarly journals Abortion Access in Ohio’s Changing Legislative Context, 2010–2018

2020 ◽  
Vol 110 (8) ◽  
pp. 1228-1234
Author(s):  
Alison H. Norris ◽  
Payal Chakraborty ◽  
Kaiting Lang ◽  
Robert B. Hood ◽  
Sarah R. Hayford ◽  
...  
Keyword(s):  
Public Health ◽  
Data Warehouse ◽  
First Trimester ◽  
The United States ◽  
Vital Statistics ◽  
Health Data ◽  
Community Survey ◽  
American Community Survey ◽  
Public Health Data ◽  
Abortion Access

Objectives. To examine abortion utilization in Ohio from 2010 to 2018, a period when more than 15 abortion-related laws became effective. Methods. We evaluated changes in abortion rates and ratios examining gestation, geographic distribution, and abortion method in Ohio from 2010 to 2018. We used data from Ohio’s Office of Vital Statistics, the Centers for Disease Control and Prevention’s Abortion Surveillance Reports, the American Community Survey, and Ohio’s Public Health Data Warehouse. Results. During 2010 through 2018, abortion rates declined similarly in Ohio, the Midwest, and the United States. In Ohio, the proportion of early first trimester abortions decreased; the proportion of abortions increased in nearly every later gestation category. Abortion ratios decreased sharply in most rural counties. When clinics closed, abortion ratios dropped in nearby counties. Conclusions. More Ohioans had abortions later in the first trimester, compared with national patterns, suggesting delays to care. Steeper decreases in abortion ratios in rural versus urban counties suggest geographic inequity in abortion access. Public Health Implications. Policies restricting abortion access in Ohio co-occur with delays to care and increasing geographic inequities. Restrictive policies do not improve reproductive health.

scholarly journals COULD CHASING GRANDKIDS KEEP US YOUNG? THE ASSOCIATION BETWEEN CUSTODIAL GRANDPARENT STATUS AND HEALTH

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S670-S670
Author(s):  
Danielle K Nadorff ◽  
Emily A Williamson ◽  
Ian T McKay
Keyword(s):  
Negative Impact ◽  
Binary Logistic Regression ◽  
The United States ◽  
Community Survey ◽  
Clinical Implications ◽  
Regression Analyses ◽  
Custodial Grandparents ◽  
Older Adulthood ◽  
Primary Responsibility ◽  
Using Data

Abstract There are approximately 7.2 million grandparents living with their grandchildren in the United States. Of these, roughly 2.5 million are skipped-generation households in which grandparents are solely responsible for meeting the needs of their grandchildren (U.S. Census, 2017). Previous research has established that custodial grandparents suffer from added strain and burden compared to their peers, which negatively impacts their health (Lo, M., Liu, Y., 2009). A decline in functional ability has a negative impact on not only the lives of these older adult grandparents but also their family members who are dependent upon them for care. The current study examines adults aged 65 and older using data from the American Community Survey 2016 to assess the extent to which raising one’s grandchildren is associated with five areas commonly subject to decline in older adulthood: cognitive performance, self-care ability, ambulatory difficulty, hearing, and vision abilities. Hierarchical binary logistic regression analyses found that after controlling for the effects of age, sex, race, and income-to-poverty ratio, custodial grandparents (those who reported having primary responsibility for their grandchildren in their own home with no parents present) were significantly less likely than their peers to report experiencing any of these five disabilities. Details of each model and clinical implications will be discussed.

You Are Where You Are From

2015 ◽  
Vol 5 (3) ◽  
pp. 86-89
Author(s):  
Robin Mejia
Keyword(s):  
United States ◽  
The United States ◽  
Community Survey ◽  
American Community Survey ◽  
United States Census ◽  
Using Data ◽  
The Way

Using data from the United States Census 2013 American Community Survey, Robin Mejia looks at the way geography affects a person’s health, wealth, education, and prospects in life.

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