The function stratamean estimates the population mean out of stratified samples either with or without consideration of finite population correction.

stratamean(y, h, Nh, wh, level = 0.95, eae = FALSE)

## Arguments

y vector of target variable. vector of stratifying variable. vector of sizes of every stratum, which has to be supplied in alphabetical or numerical order of the categories of h. vector of weights of every stratum, which has to be supplied in alphabetical or numerical order of the categories of h. coverage probability for confidence intervals. Default is level=0.95. TRUE for extensive output with the result in each and every stratum. Default is eae=FALSE.

## Details

If the absolute stratum sizes Nh are given, the variances are calculated with finite population correction. Otherwise, if the stratum weights wh are given, the variances are calculated without finite population correction.

## Value

The function stratamean returns a value, which is a list consisting of the components

call

is a list of call components: y target variable in sample data, h stratifying variable in sample data, Nh sizes of every stratum, wh weights of every stratum, fpc finite population correction, level coverage probability for confidence intervals

mean

mean estimate for population

se

standard error of the mean estimate for population

ci

vector of confidence interval boundaries for population

## References

Kauermann, Goeran/Kuechenhoff, Helmut (2010): Stichproben. Methoden und praktische Umsetzung mit R. Springer.

## Author

Shuai Shao and Juliane Manitz

Smean, Sprop

## Examples

# random data
testy <- rnorm(100)
testh <- c(rep("male",40), rep("female",60))
stratamean(testy, testh, wh=c(0.5, 0.5))
#>
#> stratamean object: Stratified sample mean estimate
#> Without finite population correction.
#> Mean estimate: -0.0212
#> Standard error: 0.0992
#> 95% confidence interval: [-0.2157,0.1732]
#> stratamean(testy, testh, wh=c(0.5, 0.5), eae=TRUE)
#>                 Mean         SE        CIu       CIo
#> female  -0.033409733 0.12415553 -0.2767501 0.2099306
#> male    -0.009039405 0.15477062 -0.3123842 0.2943054
#> overall -0.021224569 0.09920753 -0.2156678 0.1732186
# tax data
data(tax)
summary(tax)
#>        id         estRefund           actRefund              diff
#>  Min.   :   1   Min.   :     0.27   Min.   :     0.00   Min.   :     0.0
#>  1st Qu.:2272   1st Qu.:   124.77   1st Qu.:    76.31   1st Qu.:     0.0
#>  Median :4542   Median :   543.23   Median :   378.08   Median :     0.0
#>  Mean   :4542   Mean   :  3842.28   Mean   :  3227.43   Mean   :   614.9
#>  3rd Qu.:6812   3rd Qu.:  2246.06   3rd Qu.:  1756.24   3rd Qu.:     0.0
#>  Max.   :9083   Max.   :200504.35   Max.   :178104.99   Max.   :129520.4
#>     Class
#>  Length:9083
#>  Class :character
#>  Mode  :character
#>
#>
#>
nh <- as.vector(table(tax$Class)) wh <- nh/sum(nh) stratamean(y=tax$diff, h=as.vector(tax\$Class), wh=wh, eae=TRUE)
#>                Mean          SE        CIu         CIo
#> 1          40.36435    1.623603   37.18214    43.54655
#> 2         480.43275   24.026405  433.34186   527.52364
#> 3        3840.83780  312.559990 3228.23147  4453.44412
#> 4       11161.88331 2216.524710 6817.57471 15506.19191
#> overall   614.85125   40.010241  536.43262   693.26988