Stratified sampling applying SI design in all strata
Draws a simple random sample without replacement of size n_h in stratum h of size N_h
S.STSI(S, Nh, nh)
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 |
The selected sample is drawn according to a selection-rejection (list-sequential) algorithm in each stratum
The function returns a vector of size n=n_1+\cdots+n_H. Each element of this vector indicates the unit that was selected.
Hugo Andres Gutierrez Rojas hagutierrezro@gmail.com
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.
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## Example 1
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# 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]
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## Example 2
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# 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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.