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Complex Surveys
A Guide to Analysis Using R
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Summary
Each chapter concludes with exercises to reinforce understanding, and detailed appendices provide mathematical and computational insights. The book serves both as a textbook for upper-undergraduate and graduate courses on sampling and complex surveys, and as a practical reference for applied statisticians and researchers in social and health sciences.
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Complex Surveys
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Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?
This book is ideal for students in advanced statistics or social science courses focusing on survey methodology, as well as statisticians and practitioners who analyse complex survey data in health and social sciences settings. Familiarity with R and statistical concepts will help readers gain the most from this practical guide.
* Incorporates the use of R subroutines in the analysis ofsurveys * Realistically large, but not technologically inaccessible, datasets are showcased to illustrate the need for and utility of the Rsoftware system.
Book Hero Magic formatted this description to make it easier to read. While it's new and
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Description
A complete guide to principles and practices of 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 for traditional analyses. Complex Surveys is a practical guide to analysing this kind of data using R, the freely available and downloadable statistical programming language. As the creator of the specific survey package for R, the author provides the ultimate presentation on how to successfully use the software for analysing data from complex surveys, utilising 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, emphasis is placed on graphics, regression modelling, and two-phase designs. Additionally, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All examples and figures in the book are generated using R, and a related website provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in complexity, and detailed appendices outline additional mathematical and computational descriptions that assist readers in comparing results across various software systems.
Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It also serves as a practical reference guide for applied statisticians and practitioners in the social and health sciences who regularly use statistics in their work.
Series: Wiley Series in Survey Methodology
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Book Details
INFORMATION
ISBN: 9780470284308
Publisher: John Wiley & Sons Inc
Format: Paperback / softback
Date Published: 05 March 2010
Country: United States
Imprint: John Wiley & Sons Inc
Illustration: Charts: 10 B&W, 0 Color; Drawings: 20 B&W, 0 Color; Screen captures: 40 B&W, 0 Color; Tables: 0 B&W, 0 Color; Graphs: 110 B&W, 0 Color
Audience: Professional and scholarly
DIMENSIONS
Spine width: 20.0mm
Width: 155.0mm
Height: 231.0mm
Weight: 431g
Pages: 296
About the Author
THOMAS LUMLEY, PHD, is Associate Professor of Biostatistics at the University of Washington. He has published numerous journal articles in his areas of research interest, which include regression modeling, clinical trials, statistical computing, and survey research. Dr. Lumley created the survey package that currently accompanies the R software package, and he is also coauthor of Biostatistics: A Methodology for the Health Sciences, Second Edition, published by Wiley.
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