Elements of a sampling design

Analyzing Survey Data in R

Kelly McConville

Assistant Professor of Statistics

Simple random sampling

Map of Pennsylvania

Simple random sampling

Map of Pennsylvania with dots representing sampled residents

library(survey)
srs_design <- svydesign(data = paSample,
                        weights = ~wts,
                        fpc = ~N, id = ~1)

Simple random sampling

Map of Pennsylvania with dots representing sampled residents and both Pittburgh and Philadelphia highlighted

Simple random sampling

Map of Pennsylvania with dots representing sampled residents and both Pittburgh and Philadelphia highlighted. Warren and McKean counties are colored green.

Stratified sampling

Map of Pennsylvania with each county a different color

Stratified sampling

Map of Pennsylvania with each county a different color and dots representing sampled residents

library(survey)
stratified_design <- svydesign(data = paSample, id = ~1, weights = ~wts, 
                               strata = ~county, fpc = ~N)

Cluster sampling

Map of Pennsylvania with each county a different color

Cluster sampling

Map of Pennsylvania with the five sampled counties in black

Cluster sampling

Map of Pennsylvania with the five sampled counties in black and dots representing sampled residents

library(survey)
cluster_design <- svydesign(data = paSample, id = ~county + personid, 
                            fpc = ~N1 + N2, weights = ~wts)

Let's practice!

Analyzing Survey Data in R