Practical Tools for Designing and Weighting Survey Samples

Author: Richard Valliant
Publisher: Springer Science & Business Media
ISBN: 1461464498
Format: PDF, ePub, Docs
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Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least three audiences: (1) Students seeking a more in-depth understanding of applied sampling either through a second semester-long course or by way of a supplementary reference; (2) Survey statisticians searching for practical guidance on how to apply concepts learned in theoretical or applied sampling courses; and (3) Social scientists and other survey practitioners who desire insight into the statistical thinking and steps taken to design, select, and weight random survey samples. Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses.

Applied Survey Data Analysis Second Edition

Author: Steven G. Heeringa
Publisher: CRC Press
ISBN: 1351649302
Format: PDF, ePub, Docs
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Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software. Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s updated website.

Mobile Phone Panel Surveys in Developing Countries

Author: Andrew Dabalen
Publisher: World Bank Publications
ISBN: 1464809054
Format: PDF, Mobi
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Household survey data are very useful for monitoring living conditions of citizens of any country. In developing countries, a lot of this data are collected through “traditional†? face-to-face household surveys. Due to the remote and dispersed nature of many populations in developing countries, but also because of the complex nature of many survey questionnaires, collection of timely welfare data has often proved expensive and logistically challenging. Yet, there is a need for faster, cheaper to collect, lighter, more nimble data collection methods to address data gaps between big household surveys. The recent proliferation of mobile phone networks has opened new possibilities. By combining baseline data from a traditional household survey with subsequent interviews of selected respondents using mobile phones, this facilitates welfare monitoring and opinion polling almost real time. The purpose of this handbook is to contribute to the development of the new field of mobile phone data collection in developing countries. The handbook documents how this innovative approach to data collection works, its advantages and challenges. The handbook draws primarily from the authors’ first-hand experiences with mobile phone surveys in Africa and also benefits from experiences elsewhere. It is intended to serve a diverse audience including those involved in collecting (representative) data using mobile phones, and those using data collected through this approach. For those who will be implementing a mobile phone panel survey, the different chapters guide them through every stage of the implementation process. For potential users of the data collected via mobile phone technology, the handbook presents a new approach to data collection which they can use for monitoring programs and facilitate almost real time decision-making. A further purpose of this book is to contribute to the debate regarding the advantages of the method as well as the challenges associated with it.

Complex Surveys

Author: Thomas Lumley
Publisher: John Wiley & Sons
ISBN: 111821093X
Format: PDF, Mobi
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A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.

Survey Weights

Author: Richard Valliant
Publisher:
ISBN: 9781597182607
Format: PDF, ePub
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Survey Weights: A Step-by-Step Guide to Calculation is the first guide geared toward Stata users that systematically covers the major steps taken in creating survey weights. These weights are used to project a sample to some larger population and can be computed for either probability or nonprobability samples. Sample designs can range from simple, single-stage samples to more complex, multistage samples, each of which may use specialized steps in weighting to account for selection probabilities, nonresponse, inaccurate coverage of a population by a sample, and auxiliary data to improve precision and compensate for coverage errors. The authors provide many examples with Stata code.

Statistics for Real Life Sample Surveys

Author: Sergey Dorofeev
Publisher: Cambridge University Press
ISBN: 113945854X
Format: PDF, Docs
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Samples used in social and commercial surveys, especially of the general population, are usually less random (often by design) than many people using them realise. Unless it is understood, this 'non-randomness' can compromise the conclusions drawn from the data. This book introduces the challenges posed by less-than-perfect samples, giving background knowledge and practical guidance for those who have to deal with them. It explains why samples are, and sometimes should be, non-random in the first place; how to assess the degree of non-randomness; when correction by weighting is appropriate and how to apply it; and how the statistical treatment of these samples must be adapted. Extended data examples show the techniques at work. This is a book for practising researchers. It is a reference for the methods and formulae needed to deal with commonly encountered situations and, above all, a source of realistic and implementable solutions.

The Palgrave Handbook of Survey Research

Author: David L. Vannette
Publisher: Springer
ISBN: 3319543954
Format: PDF, ePub, Mobi
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This handbook is a comprehensive reference guide for researchers, funding agencies and organizations engaged in survey research. Drawing on research from a world-class team of experts, this collection addresses the challenges facing survey-based data collection today as well as the potential opportunities presented by new approaches to survey research, including in the development of policy. It examines innovations in survey methodology and how survey scholars and practitioners should think about survey data in the context of the explosion of new digital sources of data. The Handbook is divided into four key sections: the challenges faced in conventional survey research; opportunities to expand data collection; methods of linking survey data with external sources; and, improving research transparency and data dissemination, with a focus on data curation, evaluating the usability of survey project websites, and the credibility of survey-based social science. Chapter 23 of this book is open access under a CC BY 4.0 license at link.springer.com.

Complex Survey Data Analysis with SAS

Author: Taylor H. Lewis
Publisher: CRC Press
ISBN: 1315349779
Format: PDF, ePub, Mobi
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Complex Survey Data Analysis with SAS® is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors. After clearly explaining how the presence of these features can invalidate the assumptions underlying most traditional statistical techniques, this book equips readers with the knowledge to confidently account for them during the estimation and inference process by employing the SURVEY family of SAS/STAT® procedures. The book offers comprehensive coverage of the most essential topics, including: Drawing random samples Descriptive statistics for continuous and categorical variables Fitting and interpreting linear and logistic regression models Survival analysis Domain estimation Replication variance estimation methods Weight adjustment and imputation methods for handling missing data The easy-to-follow examples are drawn from real-world survey data sets spanning multiple disciplines, all of which can be downloaded for free along with syntax files from the author’s website: http://mason.gmu.edu/~tlewis18/. While other books may touch on some of the same issues and nuances of complex survey data analysis, none features SAS exclusively and as exhaustively. Another unique aspect of this book is its abundance of handy workarounds for certain techniques not yet supported as of SAS Version 9.4, such as the ratio estimator for a total and the bootstrap for variance estimation. Taylor H. Lewis is a PhD graduate of the Joint Program in Survey Methodology at the University of Maryland, College Park, and an adjunct professor in the George Mason University Department of Statistics. An avid SAS user for 15 years, he is a SAS Certified Advanced programmer and a nationally recognized SAS educator who has produced dozens of papers and workshops illustrating how to efficiently and effectively conduct statistical analyses using SAS.

Encyclopedia of Research Design

Author: Neil J. Salkind
Publisher: SAGE
ISBN: 1412961270
Format: PDF, Docs
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"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.

Statistical Methods for Psychology

Author: David Howell
Publisher: Cengage Learning
ISBN: 1111835489
Format: PDF, Kindle
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STATISTICAL METHODS FOR PSYCHOLOGY surveys the statistical techniques commonly used in the behavioral and social sciences, particularly psychology and education. To help students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text, author David Howell emphasizes conceptual understanding. This Eighth Edition continues to focus students on two key themes that are the cornerstones of this book’s success: the importance of looking at the data before beginning a hypothesis test, and the importance of knowing the relationship between the statistical test in use and the theoretical questions being asked by the experiment. New and expanded topics--reflecting the evolving realm of statistical methods--include effect size, meta-analysis, and treatment of missing data. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.