Bolstad (version 0.1-9)

sscsample: Simple, Stratified and Cluster Sampling

Description

Samples from a fixed population using either simple random sampling, stratitified sampling or cluster sampling.

Usage

sscsample(size, n.samples, sample.type="simple", x = NULL, strata = NULL, cluster = NULL, ret=FALSE)

Arguments

size

the desired size of the sample

n.samples

the number of repeat samples to take

sample.type

the sampling method. Can be one of "simple", "stratified", "cluser" or 1, 2, 3 where 1 corresponds to "simple", 2 to "stratified" and 3 to "cluster"

x

a vector of measurements for each unit in the population. By default x is not used, and the builtin data set sscsample.data is used

strata

a corresponding vector for each unit in the population indicating membership to a stratum

cluster

a corresponding vector for each unit in the population indicating membership to a cluster

ret

if true then the samples, their means, and the numbers of observations from each stratum are returned as a list.

Value

• If ret is true, then a list will be returned with the following components:
• samples
  a matrix with the number of rows equal to size and the number of columns equal to n.samples. Each column corresponds to a sample drawn from the population
• s.strata
  a matrix showing how many units from each stratum were included in the sample
• means
  a vector containing the mean of each sample drawn

See Also

sscsample.data

Examples

## Draw 200 samples of size 20 using simple random sampling
sscsample(20,200)

## Draw 200 samples of size 20 using simple random sampling and store the
## results. Extract the means of all 200 samples, and the 50th sample 
res<-sscsample(20,200,ret=TRUE)
res$means
res$samples[,50]