S.STSI {TeachingSampling}

Stratified sampling applying SI design in all strata

Description

Draws a simple random sample without replacement of size n_h in stratum h of size N_h

Usage

S.STSI(S, Nh, nh)

Arguments

S

Vector identifying the membership to the strata of each unit in the population

Nh

Vector of stratum sizes

nh

Vector of sample size in each stratum

Details

The selected sample is drawn according to a selection-rejection (list-sequential) algorithm in each stratum

Value

The function returns a vector of size n=n_1+\cdots+n_H. Each element of this vector indicates the unit that was selected.

Author(s)

Hugo Andres Gutierrez Rojas [e-mail]

References

Sarndal, C-E. and Swensson, B. and Wretman, J. (1992), Model Assisted Survey Sampling. Springer.
Gutierrez, H. A. (2009), Estrategias de muestreo: Diseno de encuestas y estimacion de parametros. Editorial Universidad Santo Tomas.

See Also

E.STSI

Examples

############
## Example 1
############
# Vector U contains the label of a population of size N=5
U <- c("Yves", "Ken", "Erik", "Sharon", "Leslie")
# Vector Strata contains an indicator variable of stratum membership 
Strata <- c("A", "A", "A", "B", "B")
Strata
# The stratum sizes
Nh <- c(3,2)
# Then sample size in each stratum
nh <- c(2,1)
# Draws a stratified simple random sample without replacement of size n=3
sam <- S.STSI(Strata, Nh, nh)
sam
# The selected sample is
U[sam]

############
## Example 2
############
# Uses the Lucy data to draw a stratified random sample
#  accordind to a SI design in each stratum
data(Lucy)
attach(Lucy)
# Level is the stratifying variable
summary(Level)
# Defines the size of each stratum
N1<-summary(Level)[[1]]
N2<-summary(Level)[[2]]
N3<-summary(Level)[[3]]
N1;N2;N3
Nh <- c(N1,N2,N3)
# Defines the sample size at each stratum
n1<-70
n2<-100
n3<-200
nh<-c(n1,n2,n3)
# Draws a stratified sample
sam <- S.STSI(Level, Nh, nh)
# The information about the units in the sample is stored in an object called data
data <- Lucy[sam,]
data
dim(data)