trimWeights: Trim sampling weights

In survey: Analysis of Complex Survey Samples

Trim sampling weights

Description

Trims very high or very low sampling weights to reduce the influence of outlying observations. In a replicate-weight design object, the replicate weights are also trimmed. The total amount trimmed is divided among the observations that were not trimmed, so that the total weight remains the same.

Usage

trimWeights(design, upper = Inf, lower = -Inf, ...)
## S3 method for class 'survey.design2'
trimWeights(design, upper = Inf, lower = -Inf, strict=FALSE,...)
## S3 method for class 'svyrep.design'
trimWeights(design, upper = Inf, lower = -Inf,
strict=FALSE, compress=FALSE,...)

Arguments

design	A survey design object
upper	Upper bound for weights
lower	Lower bound for weights
strict	The reapportionment of the ‘trimmings’ from the weights can push other weights over the limits. If trim=TRUE the function repeats the trimming iteratively to prevent this. For replicate-weight designs strict applies only to the trimming of the sampling weights.
compress	Compress the replicate weights after trimming.
...	Other arguments for future expansion

Value

A new survey design object with trimmed weights.

See Also

calibrate has a trim option for trimming the calibration adjustments.

Examples

data(api)
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)

pop.totals<-c(`(Intercept)`=6194, stypeH=755, stypeM=1018,
api99=3914069)
dclus1g<-calibrate(dclus1, ~stype+api99, pop.totals)

summary(weights(dclus1g))
dclus1t<-trimWeights(dclus1g,lower=20, upper=45)
summary(weights(dclus1t))
dclus1tt<-trimWeights(dclus1g, lower=20, upper=45,strict=TRUE)
summary(weights(dclus1tt))


svymean(~api99+api00+stype, dclus1g)
svymean(~api99+api00+stype, dclus1t)
svymean(~api99+api00+stype, dclus1tt)

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