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A thorough and comprehensive guide to the theoretical, practical, and methodological approaches used in survey experiments across disciplines such as political science, health sciences, sociology, economics, psychology, and marketing This book explores and explains the broad range of experimental designs embedded in surveys that use both probability and non-probability samples. It approaches the usage of survey-based experiments with a Total Survey Error (TSE) perspective, which provides insight on the strengths and weaknesses of the techniques used. Experimental Methods in Survey Research: Techniques that Combine Random Sampling with Random Assignment addresses experiments on within-unit coverage, reducing nonresponse, question and questionnaire design, minimizing interview measurement bias, using adaptive design, trend data, vignettes, the analysis of data from survey experiments, and other topics, across social, behavioral, and marketing science domains. Each chapter begins with a description of the experimental method or application and its importance, followed by reference to relevant literature. At least one detailed original experimental case study then follows to illustrate the experimental method's deployment, implementation, and analysis from a TSE perspective. The chapters conclude with theoretical and practical implications on the usage of the experimental method addressed. In summary, this book: Fills a gap in the current literature by successfully combining the subjects of survey methodology and experimental methodology in an effort to maximize both internal validity and external validity Offers a wide range of types of experimentation in survey research with in-depth attention to their various methodologies and applications Is edited by internationally recognized experts in the field of survey research/methodology and in the usage of survey-based experimentation -featuring contributions from across a variety of disciplines in the social and behavioral sciences Presents advances in the field of survey experiments, as well as relevant references in each chapter for further study Includes more than 20 types of original experiments carried out within probability sample surveys Addresses myriad practical and operational aspects for designing, implementing, and analyzing survey-based experiments by using a Total Survey Error perspective to address the strengths and weaknesses of each experimental technique and method Experimental Methods in Survey Research: Techniques that Combine Random Sampling with Random Assignment is an ideal reference for survey researchers and practitioners in areas such political science, health sciences, sociology, economics, psychology, public policy, data collection, data science, and marketing. It is also a very useful textbook for graduate-level courses on survey experiments and survey methodology. Paul J. Lavrakas, PhD, is Senior Fellow at the NORC at the University of Chicago, Adjunct Professor at University of Illinois-Chicago, Senior Methodologist at the Social Research Centre of Australian National University and at the Office for Survey Research at Michigan State University. Michael W. Traugott, PhD, is Research Professor in the Institute for Social Research at the University of Michigan. Courtney Kennedy, PhD, is Director of Survey Research at Pew Research Center in Washington, DC. Allyson L. Holbrook, PhD, is Professor of Public Administration and Psychology at the University of Illinois-Chicago. Edith D. de Leeuw, PhD, is Professor of Survey Methodology in the Department of Methodology and Statistics at Utrecht University. Brady T. West, PhD, is Research Associate Professor in the Survey Research Center at the University of Michigan-Ann Arbor.

The American Community Survey (ACS) was conceptualized as a replacement to the census long form, which collected detailed population and housing data from a sample of the U.S. population, once a decade, as part of the decennial census operations. The long form was traditionally the main source of socio-economic information for areas below the national level. The data provided for small areas, such as counties, municipalities, and neighborhoods is what made the long form unique, and what makes the ACS unique today. Since the successful transition from the decennial long form in 2005, the ACS has become an invaluable resource for many stakeholders, particularly for meeting national and state level data needs. However, due to inadequate sample sizes, a major challenge for the survey is producing reliable estimates for smaller geographic areas, which is a concern because of the unique role fulfilled by the long form, and now the ACS, of providing data with a geographic granularity that no other federal survey could provide. In addition to the primary challenge associated with the reliability of the estimates, this is also a good time to assess other aspects of the survey in order to identify opportunities for refinement based on the experience of the first few years. Realizing the Potential of the American Community Survey provides input on ways of improving the ACS, focusing on two priority areas: identifying methods that could improve the quality of the data available for small areas, and suggesting changes that would increase the survey's efficiency in responding to new data needs. This report considers changes that the ACS office should consider over the course of the next few years in order to further improve the ACS data. The recommendations of Realizing the Potential of the American Community Survey will help the Census Bureau improve performance in several areas, which may ultimately lead to improved data products as the survey enters its next decade.

The National Research Council of the National Academies was requested by the National Aeronautics and Space Administration (NASA) to perform an independent assessment of NASA's National Aviation Operations Monitoring Service (NAOMS) project, which was a survey administered to pilots from April 2001 through December 2004.The NRC reviewed various aspects of the NAOMS project, including the survey methodology, and conducted a limited analysis of the publicly available survey data. An Assessment of NASA's National Aviation Operations Monitoring Service presents the resulting analyses and findings.

The Pew Research Center’s survey, Jewish Americans in 2020, was designed to provide estimates of the size of the US Jewish population, sociodemographic data on issues such as intermarriage, child-rearing, engagement in Jewish communal life, and a description of American Jewish attitudes. A sophisticated sample design was employed to ensure accurate and generalizable assessments of the population. Because Jews are a small sub-group and the US government does not collect census data on religious groups, creating estimates is a non-trivial task. The focus of this paper is on the validity of Pew’s estimate of 7.5 million US Jewish adults and children, 2.4% of the overall US population. The estimate is an important standalone indicator and is the basis for assessments of current Jewish attitudes and behavior. This paper considers the underlying construct of Jewish identity and its operationalization by Pew and evaluates the convergent validity of Pew’s findings. The efforts to define “who is a Jew” in sociodemographic surveys is described, and a set of methodological challenges to creating estimates are considered. The results of this review indicate that Pew’s criteria for inclusion in the population estimate comports with long-standing views of how to assess the Jewish population. Furthermore, Pew’s estimate of 7.5 million Jewish Americans is consistent with other recent demographic studies of the population. Their conclusions about a growing US Jewish population suggest a new narrative of American Jewish life that reflects the diversity of ways in which Jewish identity is expressed.

The U.S. Census Bureau maintains an important portfolio of economic statistics programs, including quinquennial economic censuses, annual economic surveys, and quarterly and monthly indicator surveys. Government, corporate, and academic users rely on the data to understand the complexity and dynamism of the U.S. economy. Historically, the Bureau's economic statistics programs developed sector by sector (e.g., separate surveys of manufacturing, retail trade, and wholesale trade), and they continue to operate largely independently. Consequently, inconsistencies in questionnaire content, sample and survey design, and survey operations make the data not only more difficult to use, but also more costly to collect and process and more burdensome to the business community than they could be. This report reviews the Census Bureau's annual economic surveys. Specifically, it examines the design, operations, and products of 11 surveys and makes recommendations to enable them to better answer questions about the evolving economy.

Reform of welfare is one of the nation's most contentious issues, with debate often driven more by politics than by facts and careful analysis. Evaluating Welfare Reform in an Era of Transition identifies the key policy questions for measuring whether our changing social welfare programs are working, reviews the available studies and research, and recommends the most effective ways to answer those questions. This book discusses the development of welfare policy, including the landmark 1996 federal law that devolved most of the responsibility for welfare policies and their implementation to the states. A thorough analysis of the available research leads to the identification of gaps in what is currently known about the effects of welfare reform. Evaluating Welfare Reform in an Era of Transition specifies what-and why-we need to know about the response of individual states to the federal overhaul of welfare and the effects of the many changes in the nation's welfare laws, policies, and practices. With a clear approach to a variety of issues, Evaluating Welfare Reform in an Era of Transition will be important to policy makers, welfare administrators, researchers, journalists, and advocates on all sides of the issue.

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 Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) of 1996 fundamentally changed the nation's social welfare system, replacing a federal entitlement program for low-income families, called Aid to Families with Dependent Children (AFDC), with state-administered block grants, the Temporary Assistance for Needy Families (TANF) program. PRWORA furthered a trend started earlier in the decade under so called \"waiver\" programs-state experiments with different types of AFDC rules-toward devolution of design and control of social welfare programs from the federal government to the states. The legislation imposed several new, major requirements on state use of federal welfare funds but otherwise freed states to reconfigure their programs as they want. The underlying goal of the legislation is to decrease dependence on welfare and increase the self-sufficiency of poor families in the United States. In summer 1998, the Office of the Assistant Secretary for Planning and Evaluation (ASPE) of the Department of Health and Human Services (DHHS) asked the Committee on National Statistics of the National Research Council to convene a Panel on Data and Methods for Measuring the Effects of Changes in Social Welfare Programs. The panel's overall charge is to study and make recommendations on the best strategies for evaluating the effects of PRWORA and other welfare reforms and to make recommendations on data needs for conducting useful evaluations. This interim report presents the panel's initial conclusions and recommendations. Given the short length of time the panel has been in existence, this report necessarily treats many issues in much less depth than they will be treated in the final report. The report has an immediate short-run goal of providing DHHS-ASPE with recommendations regarding some of its current projects, particularly those recently funded to study \"welfare leavers\"-former welfare recipients who have left the welfare rolls as part of the recent decline in welfare caseloads.

Differences of opinion regarding the numerical size of US Jewry are discussed in this article, with special reference to the 2020 Pew survey of Jewish Americans. Issues discussed involve understanding the theoretical assumptions, technical requirements, and accumulated body of knowledge of Jewish demography and population studies as a discipline; the different methods and biases of Jewish social survey research; the variety of possible Jewish population definitions in a world which is no more dichotomous; the essential role children's Jewish socialization in Jewish population estimates; the independence vs. circularity of existing Jewish population estimates. It is argued that different possible estimates can coexist side-by-side, provided assumptions, methods and definitions are fully transparent and amenable to clear common denominators. The study of US Jews cannot be severed from the study of Jews globally.