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, and representative 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 * A new chapter on nonprobability sampling *
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 Nurnberg, 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.
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