In the early 1990s, the Census Bureau proposed a program of continuous measurement as a possible alternative to the gathering of detailed social, economic, and housing data from a sample of the U.S. population as part of the decennial census. The American Community Survey (ACS) became a reality in 2005, and has included group quarters (GQ)-such places as correctional facilities for adults, student housing, nursing facilities, inpatient hospice facilities, and military barracks-since 2006, primarily to more closely replicate the design and data products of the census long-form sample. The decision to include group quarters in the ACS enables the Census Bureau to provide a comprehensive benchmark of the total U.S. population (not just those living in households). However, the fact that the ACS must rely on a sample of what is a small and very diverse population, combined with limited funding available for survey operations, makes the ACS GQ sampling, data collection, weighting, and estimation procedures more complex and the estimates more susceptible to problems stemming from these limitations. The concerns are magnified in small areas, particularly in terms of detrimental effects on the total population estimates produced for small areas. Small Populations, Large Effects provides an in-depth review of the statistical methodology for measuring the GQ population in the ACS. This report addresses difficulties associated with measuring the GQ population and the rationale for including GQs in the ACS. Considering user needs for ACS data and of operational feasibility and compatibility with the treatment of the household population in the ACS, the report recommends alternatives to the survey design and other methodological features that can make the ACS more useful for users of small-area data.

The usefulness of the U.S. decennial census depends critically on the accuracy with which individual people are counted in specific housing units, at precise geographic locations. The 2000 and other recent censuses have relied on a set of residence rules to craft instructions on the census questionnaire in order to guide respondents to identify their correct "usual residence." Determining the proper place to count such groups as college students, prisoners, and military personnel has always been complicated and controversial; major societal trends such as placement of children in shared custody arrangements and the prevalence of "snowbird" and "sunbird" populations who regularly move to favorable climates further make it difficult to specify ties to one household and one place. Once, Only Once, and in the Right Place reviews the evolution of current residence rules and the way residence concepts are presented to respondents. It proposes major changes to the basic approach of collecting residence information and suggests a program of research to improve the 2010 and future censuses.

Combining the power of professional, GIS-based cartography with the most up-to-date data, this book presents a new perspective on America's demographic landscape.

This open access book describes the differences in US census coverage, also referred to as “differential undercount”, by showing which groups have the highest net undercounts and which groups have the greatest undercount differentials, and discusses why such undercounts occur. In addition to focusing on measuring census coverage for several demographic characteristics, including age, gender, race, Hispanic origin status, and tenure, it also considers several of the main hard-to-count populations, such as immigrants, the homeless, the LBGT community, children in foster care, and the disabled. However, given the dearth of accurate undercount data for these groups, they are covered less comprehensively than those demographic groups for which there is reliable undercount data from the Census Bureau. This book is of interest to demographers, statisticians, survey methodologists, and all those interested in census coverage.

Exploring the U.S. Census gives social science students and researchers the tools to understand, extract, process, and analyze census data, including the American Community Survey and other datasets. This text provides background on the data collection methods, structures, and potential pitfalls for unfamiliar researchers with applied exercises and software walk-throughs.