svyqqplot: Quantile-quantile plots for survey data

In survey: Analysis of Complex Survey Samples

Quantile-quantile plots for survey data

Description

Quantile-quantile plots either against a specified distribution function or comparing two variables from the same or different designs.

Usage

svyqqplot(formula, design, designx = NULL, na.rm = TRUE, qrule = "hf8",
    xlab = NULL, ylab = NULL, ...)
svyqqmath(x, design, null=qnorm, na.rm=TRUE, xlab="Expected",ylab="Observed",...)

Arguments

x, formula	A one-sided formula for svyqqmath or a two-sided formula for svyqqplot
design	Survey design object to look up variables
designx	Survey design object to look up the RHS variable in svyqqplot, if different from the LHS variable
null	Quantile function to compare the data quantiles to
na.rm	Remove missing values
qrule	How to define quantiles for svyqqplot – see svyquantile for possible values
xlab, ylab	Passed to plot. For svyqqplot, if these are NULL they are replaced by the variable names
...	Graphical options to be passed to plot

Value

None

See Also

quantile qqnorm qqplot

Examples

data(api)

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

svyqqmath(~api99, design=dstrat)
svyqqplot(api00~api99, design=dstrat)

dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
opar<-par(mfrow=c(1,2))

## sample distributions very different
qqplot(apiclus1$enroll, apistrat$enroll); abline(0,1)

## estimated population distributions much more similar
svyqqplot(enroll~enroll, design=dstrat,designx=dclus1,qrule=survey:::qrule_hf8); abline(0,1)
par(opar)

survey documentation built on May 29, 2024, 12:05 p.m.