ABSTRACT
A survey may be stratified with several stages of clustering and then be calibrated to population quantities. Design effects, which describe the effects of the survey design on variances of estimates, are commonly used when planning surveys. This chapter shows how to compute estimates of population means, totals, quantiles, and design effects for complex surveys using data from the U.S. National Health and Nutrition Examination Survey. Example code also illustrates how to use functions from base R and contributed packages to produce a variety of histograms, boxplots, scatterplots, and smoothed trend lines for survey data.
