Practical Tools for Designing and Weighting Survey Samples

Beschreibung

The goal of this book is to put an array of tools at the fingertips of students, practitioners, and researchers 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 volume serves at least three audiences: (1) students of applied sampling techniques; 2) practicing survey statisticians applying concepts learned in theoretical or applied sampling courses; and (3) social scientists and other survey practitioners who design, select, and weight survey samples.

The text thoroughly covers fundamental aspects of survey sampling, such as sample size calculation (with examples for both single- and multi-stage sample design) and weight computation, accompanied by software examples to facilitate implementation. Features include step-by-step instructions for calculating survey weights, extensive real-world examples and applications, andrepresentative programming code in R, SAS, and other packages.

Since the publication of the first edition in 2013, there have been important developments in making inferences from nonprobability samples, in address-based sampling (ABS), and in the application of machine learning techniques for survey estimation. New to this revised and expanded edition:

•           Details on new functions in the PracTools package

•           Additional machine learning methods to form weighting classes

•           New coverage of nonlinear optimization algorithms for sample allocation

•           Reflecting effects of multiple weighting steps (nonresponse and calibration) on standard errors

•           Additional examples, exercises, and updated references throughout

Richard Valliant, PhD, is Research Professor Emeritus at the Institute for Social Research at the University of Michigan and at the Joint Program in Survey Methodology at the University of Maryland. He is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and has been an Associate Editor of the Journal of the American Statistical Association, Journal of Official Statistics, and Survey Methodology.   

Jill A. Dever, PhD, is Senior Research Statistician at RTI International in Washington, DC. She is a Fellow of the American Statistical Association, Associate Editor for Survey Methodology and the Journal of Official Statistics, and an Assistant Research Professor in the Joint Program in Survey Methodology at the University of Maryland. She has served on several panels for the National Academy of Sciences and as a task force member for the American Association of Public Opinion Research’s report on nonprobability sampling.

Frauke Kreuter, PhD, is Professor and Director of the Joint Program in Survey Methodology at the University of Maryland, Professor of Statistics and Methodology at the University of Mannheim, and Head of the Statistical Methods Research Department at the Institute for Employment Research (IAB) in Nürnberg, Germany. She is a Fellow of the American Statistical Association and has been Associate Editor of the Journal of the Royal Statistical Society,Journal of Official Statistics, Sociological Methods and Research, Survey Research Methods, Public Opinion Quarterly, American Sociological Review, and the Stata Journal. She is founder of the International Program for Survey and Data Science and co-founder of the Coleridge Initiative.

• Step-by-step instructions for calculating survey weights 
  
• Extensive real-world examples and applications throughout 
  
• Demonstrates how to use existing software to solve survey problems
• The most up-to-date textbook and professional reference for statistical survey sampling

Autor*in

Richard Valliant

Themen in »Practical Tools for Designing and Weighting Survey Samples«

address-based sampling area probability sampling balanced repeated replication bootstrap calibration estimation general regression estimation jackknife variance estimation machine learning mathematical programming multiphase designs multistage sampling non-probability samples nonresponse adjustment poststratification power calculations

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“This book attempts to explain long used approaches, illustrate how existing software can be used to solve survey problems, and develop some specialized software where needed with a focus on related practitioners (i.e. students, survey statisticians, and other survey practitioners). … this book may be useful to students, survey statisticians, social scientists and other survey practitioners. The book may also serve as a useful reference for other professionals engaged in the conduct of sample surveys.” (Sada Nand Dwivedi, ISCB News, iscb.info, Issue 67, June, 2019)
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