Examines the different populations and settings that can make surveys hard to conduct and discusses methods to meet these challenges.

The increasing diversity of population of the United States presents many challenges to conducting health research that is representative and informative. Dispersion and accessibility issues can increase logistical costs; populations for which it is difficult to obtain adequate sample size are also likely to be expensive to study. Hence, even if it is technically feasible to study a small population, it may not be easy to obtain the funding to do so. In order to address the issues associated with improving health research of small populations, the National Academies of Sciences, Engineering, and Medicine convened a workshop in January 2018. Participants considered ways of addressing the challenges of conducting epidemiological studies or intervention research with small population groups, including alternative study designs, innovative methodologies for data collection, and innovative statistical techniques for analysis.

The reported population of American Indians and Alaska Natives has grown rapidly over the past 20 years. These changes raise questions for the Indian Health Service and other agencies responsible for serving the American Indian population. How big is the population? What are its health care and insurance needs? This volume presents an up-to-date summary of what is known about the demography of American Indian and Alaska Native populationâ€"their age and geographic distributions, household structure, employment, and disability and disease patterns. This information is critical for health care planners who must determine the eligible population for Indian health services and the costs of providing them. The volume will also be of interest to researchers and policymakers concerned about the future characteristics and needs of the American Indian population.

This book is the reference on indirect sampling and the generalised weight share method. It reviews the different developments done by the author on these subjects. In addition to the underlying theory, the book presents different possible applications that drive its interest. The reader will find in this book the answer to questions that come, inevitably, when working in a context of indirect sampling.

Population-based survey experiments have become an invaluable tool for social scientists struggling to generalize laboratory-based results, and for survey researchers besieged by uncertainties about causality. Thanks to technological advances in recent years, experiments can now be administered to random samples of the population to which a theory applies. Yet until now, there was no self-contained resource for social scientists seeking a concise and accessible overview of this methodology, its strengths and weaknesses, and the unique challenges it poses for implementation and analysis. Drawing on examples from across the social sciences, this book covers everything you need to know to plan, implement, and analyze the results of population-based survey experiments. But it is more than just a "how to" manual. This lively book challenges conventional wisdom about internal and external validity, showing why strong causal claims need not come at the expense of external validity, and how it is now possible to execute experiments remotely using large-scale population samples. Designed for social scientists across the disciplines, Population-Based Survey Experiments provides the first complete introduction to this methodology. Offers the most comprehensive treatment of the subject Features a wealth of examples and practical advice Reexamines issues of internal and external validity Can be used in conjunction with downloadable data from ExperimentCentral.org for design and analysis exercises in the classroom

This volume, a companion to Evaluating Welfare Reform in an Era of Transition, is a collection of papers on data collection issues for welfare and low-income populations. The papers on survey issues cover methods for designing surveys taking into account nonresponse in advance, obtaining high response rates in telephone surveys, obtaining high response rates in in-person surveys, the effects of incentive payments, methods for adjusting for missing data in surveys of low-income populations, and measurement error issues in surveys, with a special focus on recall error. The papers on administrative data cover the issues of matching and cleaning, access and confidentiality, problems in measuring employment and income, and the availability of data on children. The papers on welfare leavers and welfare dynamics cover a comparison of existing welfare leaver studies, data from the state of Wisconsin on welfare leavers, and data from the National Longitudinal Survey of Youth used to construct measures of heterogeneity in the welfare population based on the recipient's own welfare experience. A final paper discusses qualitative data.

This book shows readers how to select & use the most appropriate sampling methods for their survey. It covers myriad sampling techniques, and describes criteria, the logic in estimating standard errors, and how to calculate the response rate.