Stratified Sampling

Integrating a stratified structure in the population in a sampling design can considerably reduce the variance of the Horvitz-Thompson estimator. We propose in this package different methods to handle the selection of a balanced sample in stratified population. For more details see Raphaël Jauslin, Esther Eustache and Yves Tillé (2021) https://arxiv.org/abs/2101.05568.

Build

Installation

Latest version

You can install the latest version of the package StratifiedSampling with the following command:

# install.packages("devtools")
devtools::install_github("Rjauslin/StratifiedSampling")

Simple example

This basic example shows you how to set up a stratified sampling design. The example is done on the swissmunicipalities dataset from the package sampling.

library(sampling)
library(StratifiedSampling)
#> Loading required package: Matrix
#> 
#> Attaching package: 'StratifiedSampling'
#> The following object is masked from 'package:base':
#> 
#>     choose

data(swissmunicipalities)
swiss <- swissmunicipalities
X <- cbind(swiss$HApoly,
        swiss$Surfacesbois,
        swiss$P00BMTOT,
        swiss$P00BWTOT,
        swiss$POPTOT,
        swiss$Pop020,
        swiss$Pop2040,
        swiss$Pop4065,
        swiss$Pop65P,
        swiss$H00PTOT )

X <- X[order(swiss$REG),]
strata <- swiss$REG[order(swiss$REG)]

Strata are NUTS region of the Switzerland. Inclusion probabilities pik is set up equal within strata and such that the sum of the inclusion probabilities within strata is equal to 80.

pik <- sampling::inclusionprobastrata(strata,rep(80,7))

It remains to use the function stratifiedcube().

s <- stratifiedcube(X,strata,pik)

We can check that we have correctly selected the sample. It is balanced and have the right number of units selected in each stratum.

head(s)
#> [1] 0 0 0 0 0 0

sum(s)
#> [1] 560
t(X/pik)%*%s
#>          [,1]
#>  [1,] 4035984
#>  [2,] 1256920
#>  [3,] 3439487
#>  [4,] 3575885
#>  [5,] 7015372
#>  [6,] 1615537
#>  [7,] 2049134
#>  [8,] 2281516
#>  [9,] 1069184
#> [10,] 2974870
t(X/pik)%*%pik
#>          [,1]
#>  [1,] 3998831
#>  [2,] 1270996
#>  [3,] 3567567
#>  [4,] 3720443
#>  [5,] 7288010
#>  [6,] 1665613
#>  [7,] 2141059
#>  [8,] 2362332
#>  [9,] 1119006
#> [10,] 3115399

Xcat <- disj(strata)

t(Xcat)%*%s
#>      [,1]
#> [1,]   80
#> [2,]   80
#> [3,]   80
#> [4,]   80
#> [5,]   80
#> [6,]   80
#> [7,]   80
t(Xcat)%*%pik
#>      [,1]
#> [1,]   80
#> [2,]   80
#> [3,]   80
#> [4,]   80
#> [5,]   80
#> [6,]   80
#> [7,]   80