Description:
In this book, readers embark on an in-depth journey into conducting complex survey analysis with the {srvyr} package and tidyverse family of functions from the R programming language. Additionally, this book teaches readers how to interpret and communicate results of survey data effectively.
Review Quotes:
"I see this book being invaluable to any researcher who encounters a "survey weights" column in their dataset and isn't sure what to do with it: in part because the authors provide code for handling the weights properly but also because they stress the importance of learning how the data were collected and the impacts that sampling mechanism has on the downstream analysis. Beyond the survey statistics newbie, I also believe the book is useful to a researcher or student who has developed a methodological understanding of survey statistics and is now looking to put these topics into practice on complex survey data.[...] My favorite aspect of the book are the closing vignettes where the authors apply the concepts covered in the book to two open access datasets. In fact, the authors spend over 50 pages walking the reader through potential analyses of these data! Instead of skimming over the complexities, they devote space to helping the reader understand the layers of complexity often found in survey work and the nuances of these data, especially in terms of the estimands and survey weights."
-Kelly S. McConville in The American Statistician, March 2026