complex surveys a guide to analysis using r wiley series in survey methodology

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Complex Surveys

Author : Thomas Lumley
ISBN : 9781118210932
Genre : Mathematics
File Size : 42. 34 MB
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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.

Analysis Of Survey Data

Author : R. L. Chambers
ISBN : 9780470864395
Genre : Mathematics
File Size : 30. 58 MB
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This book is concerned with statistical methods for the analysis of data collected from a survey. A survey could consist of data collected from a questionnaire or from measurements, such as those taken as part of a quality control process. Concerned with the statistical methods for the analysis of sample survey data, this book will update and extend the successful book edited by Skinner, Holt and Smith on 'Analysis of Complex Surveys'. The focus will be on methodological issues, which arise when applying statistical methods to sample survey data and will discuss in detail the impact of complex sampling schemes. Further issues, such as how to deal with missing data and measurement of error will also be critically discussed. There have significant improvements in statistical software which implement complex sampling schemes (eg SUDAAN, STATA, WESVAR, PC CARP ) in the last decade and there is greater need for practical advice for those analysing survey data. To ensure a broad audience, the statistical theory will be made accessible through the use of practical examples. This book will be accessible to a broad audience of statisticians but will primarily be of interest to practitioners analysing survey data. Increased awareness by social scientists of the variety of powerful statistical methods will make this book a useful reference.

Practical Methods For Design And Analysis Of Complex Surveys

Author : Risto Lehtonen
ISBN : 9780470091630
Genre : Mathematics
File Size : 36. 48 MB
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Large surveys are becoming increasingly available for public use, and researchers are often faced with the need to analyse complex survey data to address key scientific issues. For proper analysis it is also important to be aware of the different aspects of the design of complex surveys. Practical Methods for Design and Analysis of Complex Surveys features intermediate and advanced statistical techniques for use in designing and analysing complex surveys. This extensively updated edition features much new material, and detailed practical exercises with links to a Web site, helping instructors and enabling use for distance learning. * Provides a comprehensive introduction to sampling and estimation in descriptive surveys, including design effect statistic and use of auxiliary data. * Includes detailed coverage of complex survey analysis, including design-based ANOVA and logistic regression with GEE estimation. * Contains much new material, including handling of non-sampling errors, and model-assisted estimation for domains. * Features detailed real-li fe case studies, such as multilevel modeling in a multinational educational survey. * Supported by a Web site containing software codes, real data sets, computerized exercises with solutions, and online training materials. Practical Methods for Design and Analysis of Complex Surveys provides a useful practical resource for researchers and practitioners working in the planning, implementation or analysis of complex surveys and opinion polls, including business, educational, health, social, and socio-economic surveys and official statistics. In addition, the book is well suited for use on intermediate and advanced courses in survey sampling.

Practical Tools For Designing And Weighting Survey Samples

Author : Richard Valliant
ISBN : 9781461464495
Genre : Social Science
File Size : 54. 82 MB
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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.

Analysis Of Questionnaire Data With R

Author : Bruno Falissard
ISBN : 9781439817674
Genre : Mathematics
File Size : 40. 85 MB
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While theoretical statistics relies primarily on mathematics and hypothetical situations, statistical practice is a translation of a question formulated by a researcher into a series of variables linked by a statistical tool. As with written material, there are almost always differences between the meaning of the original text and translated text. Additionally, many versions can be suggested, each with their advantages and disadvantages. Analysis of Questionnaire Data with R translates certain classic research questions into statistical formulations. As indicated in the title, the syntax of these statistical formulations is based on the well-known R language, chosen for its popularity, simplicity, and power of its structure. Although syntax is vital, understanding the semantics is the real challenge of any good translation. In this book, the semantics of theoretical-to-practical translation emerges progressively from examples and experience, and occasionally from mathematical considerations. Sometimes the interpretation of a result is not clear, and there is no statistical tool really suited to the question at hand. Sometimes data sets contain errors, inconsistencies between answers, or missing data. More often, available statistical tools are not formally appropriate for the given situation, making it difficult to assess to what extent this slight inadequacy affects the interpretation of results. Analysis of Questionnaire Data with R tackles these and other common challenges in the practice of statistics.

Applied Survey Data Analysis Second Edition

Author : Steven G. Heeringa
ISBN : 9781351649308
Genre : Mathematics
File Size : 79. 24 MB
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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.

Model Assisted Survey Sampling

Author : Carl-Erik Särndal
ISBN : 0387406204
Genre : Mathematics
File Size : 88. 49 MB
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Now available in paperback. This book provides a comprehensive account of survey sampling theory and methodology which will be suitable for students and researchers across a variety of disciplines. A central theme is to show how statistical modeling is a vital component of the sampling process and in the choice of estimation technique. Statistical modeling has strongly influenced sampling theory in recent years and has clarified many issues related to the uses of auxiliary information in surveys. This is the first textbook that systematically extends traditional sampling theory with the aid of a modern model assisted outlook. The central ideas of sampling theory are developed from the unifying perspective of unequal probability sampling. The book covers classical topics as well as areas where significant new developments have taken place notably domain estimation, variance estimation, methods for handling nonresponse, models for measurement error, and the analysis of survey data. The authors have taken care to presuppose nothing more on the part of the reader than a first course in statistical inference and regression analysis. Throughout, the emphasis is on statistical ideas rather than advanced mathematics. Each chapter concludes with a range of exercises incorporating the analysis of data from actual finite populations. As a result, all those concerned with survey methodology or engaged in survey sampling will find this an invaluable and up-to-date coverage of the subject.

Handbook Of Health Survey Methods

Author : Timothy P. Johnson
ISBN : 9781118002322
Genre : Business & Economics
File Size : 77. 8 MB
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A comprehensive guidebook to the current methodologies and practices used in health surveys A unique and self-contained resource, Handbook of Health Survey Methods presents techniques necessary for confronting challenges that are specific to health survey research. The handbook guides readers through the development of sample designs, data collection procedures, and analytic methods for studies aimed at gathering health information on general and targeted populations. The book is organized into five well-defined sections: Design and Sampling Issues, Measurement Issues, Field Issues, Health Surveys of Special Populations, and Data Management and Analysis. Maintaining an easy-to-follow format, each chapter begins with an introduction, followed by an overview of the main concepts, theories, and applications associated with each topic. Finally, each chapter provides connections to relevant online resources for additional study and reference. The Handbook of Health Survey Methods features: 29 methodological chapters written by highly qualified experts in academia, research, and industry A treatment of the best statistical practices and specific methodologies for collecting data from special populations such as sexual minorities, persons with disabilities, patients, and practitioners Discussions on issues specific to health research including developing physical health and mental health measures, collecting information on sensitive topics, sampling for clinical trials, collecting biospecimens, working with proxy respondents, and linking health data to administrative and other external data sources Numerous real-world examples from the latest research in the fields of public health, biomedicine, and health psychology Handbook of Health Survey Methods is an ideal reference for academics, researchers, and practitioners who apply survey methods and analyze data in the fields of biomedicine, public health, epidemiology, and biostatistics. The handbook is also a useful supplement for upper-undergraduate and graduate-level courses on survey methodology. Timothy P. Johnson, PhD, is Director of the Survey Research Laboratory and Professor of Public Administration at the University of Illinois at Chicago (UIC), where he is also Research Professor of Epidemiology and Deputy Director for Evaluation and Tracking of the UIC Center for Clinical and Translational Research. The author of numerous journal articles, Dr. Johnson is Coeditor of Survey Methods in Multicultural, Multinational, and Multiregional Contexts, also published by Wiley.

Survey Methodology And Missing Data

Author : Seppo Laaksonen
ISBN : 9783319790114
Genre : Social Science
File Size : 85. 51 MB
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This book focuses on quantitative survey methodology, data collection and cleaning methods. Providing starting tools for using and analyzing a file once a survey has been conducted, it addresses fields as diverse as advanced weighting, editing, and imputation, which are not well-covered in corresponding survey books. Moreover, it presents numerous empirical examples from the author's extensive research experience, particularly real data sets from multinational surveys.

Forest Analytics With R

Author : Andrew P. Robinson
ISBN : 1441977627
Genre : Medical
File Size : 50. 27 MB
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Forest Analytics with R combines practical, down-to-earth forestry data analysis and solutions to real forest management challenges with state-of-the-art statistical and data-handling functionality. The authors adopt a problem-driven approach, in which statistical and mathematical tools are introduced in the context of the forestry problem that they can help to resolve. All the tools are introduced in the context of real forestry datasets, which provide compelling examples of practical applications. The modeling challenges covered within the book include imputation and interpolation for spatial data, fitting probability density functions to tree measurement data using maximum likelihood, fitting allometric functions using both linear and non-linear least-squares regression, and fitting growth models using both linear and non-linear mixed-effects modeling. The coverage also includes deploying and using forest growth models written in compiled languages, analysis of natural resources and forestry inventory data, and forest estate planning and optimization using linear programming. The book would be ideal for a one-semester class in forest biometrics or applied statistics for natural resources management. The text assumes no programming background, some introductory statistics, and very basic applied mathematics.

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