svyplot: Plots for survey data

Description

Because observations in survey samples may represent very different numbers of units in the population ordinary plots can be misleading. The svyplot function produces plots adjusted in various ways for sampling weights.

Usage

svyplot(formula, design, style = c("bubble", "hex", "grayhex","subsample"),
sample.size = 500, subset = NULL, legend = 1, inches = 0.05, amount=NULL, ...)

Arguments

formula

A model formula

design

A survey object (svydesign or svrepdesign)

style

See Details below

sample.size

For style="subsample"

subset

expression using variables in the design object

legend

For style="hex" or "grayhex"

inches

Scale for bubble plots

amount

list with x and y components for amount of jittering to use in subsample plots, or NULL for the default amount

...

Passed to plot methods

Value

None

Details

Bubble plots are scatterplots with circles whose area is proportional to the sampling weight. The two "hex" styles produce hexagonal binning scatterplots, and require the hexbin package from Bioconductor. The subsample method uses the sampling weights to create a sample from approximately the population distribution and passes this to plot Bubble plots are suited to small surveys, hexagonal binning and subsampling to large surveys where plotting all the points would result in too much overlap.

Examples

Run this code

data(api)
dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)

svyplot(api00~api99, design=dstrat, style="bubble")
## these two require the hexbin package from Bioconductor
svyplot(api00~api99, design=dstrat, style="hex", xlab="1999 API",ylab="2000 API")
svyplot(api00~api99, design=dstrat, style="grayhex",legend=0)

dclus2<-svydesign(id=~dnum+snum,  weights=~pw,
                    data=apiclus2, fpc=~fpc1+fpc2)
svyplot(api00~api99, design=dclus2, style="subsample")
svyplot(api00~api99, design=dclus2, style="subsample",
          amount=list(x=25,y=25))