A complete guide to carrying out 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 to carry out traditional
analyses. "Complex Surveys" is a practical guide to the analysis of
this kind of data using R, the freely available and downloadable
statistical programming language. As creator of the specific survey
package for R, the author provides the ultimate presentation of how
to successfully use the software for analyzing data from complex
surveys while also utilizing 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, an
emphasis is placed on graphics, regression modeling, and two-phase
designs. In addition, the author supplies a unique discussion of
epidemiological two-phase designs as well as probability-weighting
for causal inference. All of the book's examples and figures are
generated using R, and a related Web site provides the R code that
allows readers to reproduce the presented content. Each chapter
concludes with exercises that vary in level of complexity, and
detailed appendices outline additional mathematical and
computational descriptions to assist readers with comparing results
from various software systems.
"Complex Surveys" is an excellent book for courses on sampling
and complex surveys at the upper-undergraduate and graduate levels.
It is also a practical reference guide for applied statisticians
and practitioners in the social and health sciences who use
statistics in their everyday work.
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