Selection of a stratified sample from the frame with srswor method

Description

Once optimal stratification has been obtained (in the dataframe 'outstrata'), and a new frame has been built by assigning to the units of the old one the new stratum labels (by means of "updateFrame" function), it is possible to select a stratified sample from the frame with the srswor method. The result of the execution of "selectSample" function is a dataframe containing selected units, with the probabilities of inclusion. It is possible to output this dataframe in a .csv file. One more .csv file is produced ("sampling check"), containing coeherence checks between (a) population in frame strata (b) population in optimised strata (c) planned units to be selected in optimised strata (d) actually selected units (e) sum of weights in each stratum

Usage

selectSample(frame, outstrata, writeFiles = FALSE,verbatim=TRUE)

Arguments

Value

A dataframe containing the sample

Author(s)

Giulio Barcaroli with contribution from Diego Zardetto

Examples

#
# The following example is realistic, but is time consuming
#
## Not run: 
library(SamplingStrata)
data(swisserrors)
data(swissstrata)
# optimisation of sampling strata
solution <- optimizeStrata ( 
    errors = swisserrors, 
    strata = swissstrata, 
    cens = NULL,
    strcens = FALSE,
    initialStrata = 3000,
    addStrataFactor = 0.01,    
    minnumstr = 2,
    iter = 60,
    pops = 20,
    mut_chance = 0.05,
    elitism_rate = 0.2,
    highvalue = 100000000,
    suggestions = NULL,
	writeFiles = FALSE)
# updating sampling strata with new strata labels
newstrata <- updateStrata(swissstrata, solution)
# updating sampling frame with new strata labels
data(swissframe)
framenew <- updateFrame(frame=swissframe,newstrata=newstrata)
# selection of sample
sample <- selectSample(frame=framenew,outstrata=solution$aggr_strata)
head(sample)

## End(Not run)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(SamplingStrata)
Loading required package: memoise
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/SamplingStrata/selectSample.Rd_%03d_medium.png", width=480, height=480)
> ### Name: selectSample
> ### Title: Selection of a stratified sample from the frame with srswor
> ###   method
> ### Aliases: selectSample
> ### Keywords: survey
> 
> ### ** Examples
> 
> #
> # The following example is realistic, but is time consuming
> #
> ## Not run: 
> ##D library(SamplingStrata)
> ##D data(swisserrors)
> ##D data(swissstrata)
> ##D # optimisation of sampling strata
> ##D solution <- optimizeStrata ( 
> ##D     errors = swisserrors, 
> ##D     strata = swissstrata, 
> ##D     cens = NULL,
> ##D     strcens = FALSE,
> ##D     initialStrata = 3000,
> ##D     addStrataFactor = 0.01,    
> ##D     minnumstr = 2,
> ##D     iter = 60,
> ##D     pops = 20,
> ##D     mut_chance = 0.05,
> ##D     elitism_rate = 0.2,
> ##D     highvalue = 100000000,
> ##D     suggestions = NULL,
> ##D 	writeFiles = FALSE)
> ##D # updating sampling strata with new strata labels
> ##D newstrata <- updateStrata(swissstrata, solution)
> ##D # updating sampling frame with new strata labels
> ##D data(swissframe)
> ##D framenew <- updateFrame(frame=swissframe,newstrata=newstrata)
> ##D # selection of sample
> ##D sample <- selectSample(frame=framenew,outstrata=solution$aggr_strata)
> ##D head(sample)
> ## End(Not run)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>