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 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 an
