mys: mean years of schooling of people with disabilities

A synthetic area-level dataset with direct estimates of the mean years of schooling of people with disabilities in 42 regencies/municipalities, 10 of which are not sampled (y = NA). Used in the examples of the area-level models; its spatial weights are mys_proxmat.

Usage

mys

Format

A data frame (tibble) with 42 rows and 9 variables:

area

area (regency/municipality) identifier, 1 to 42.

y

direct estimate of the mean years of schooling (NA for the 10 unsampled areas).

vardir

sampling variance of the direct estimate (0 for the unsampled areas, where it is not used).

rse

relative standard error of the direct estimate (%), \(100\sqrt{vardir}/y\) (0 for the unsampled areas).

x1

number of elementary schools.

x2

number of junior high schools.

x3

number of senior high schools.

n

number of people with disabilities in the Susenas sample of the area (eligible sample size; synthetic, hence not an integer, and positive also for the unsampled areas). vardir was not derived from it.

weight

sample share of the area, n / sum(n).

Source

Simulated based on empirical characteristics of the National Socio-Economic Survey (Susenas), BPS-Statistics Indonesia.

Examples

data(mys)
head(mys)
#> # A tibble: 6 × 9
#>    area     y vardir   rse    x1    x2    x3      n  weight
#>   <int> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl>  <dbl>   <dbl>
#> 1     1  8.36  0.662  9.73   124    24    14  7280. 0.0326 
#> 2     2  7.60  0.837 12.0     89    18     9  2743. 0.0123 
#> 3     3  5.51  0.882 17.0     57    19     5  1706. 0.00764
#> 4     4  3.87  0.658 21.0     88    35    19  3073. 0.0138 
#> 5     5  6.31  1.28  17.9    141    46    29 13400. 0.0600 
#> 6     6  3.93  0.388 15.9     96    29    10  2004. 0.00897
# unsampled areas
mys$area[is.na(mys$y)]
#>  [1] 21 25 26 27 28 34 35 36 37 41