Variance of food insecurity prevalence by region, calculated from bfa_eas. Used for demonstrating Neyman optimal allocation in stratified sampling.
Format
A tibble with 13 rows and 2 columns:
- region
Factor. Region name
- var
Numeric. Variance of food insecurity prevalence within region
Examples
# View the variance data
bfa_eas_variance
#> # A tibble: 13 × 2
#> region var
#> <fct> <dbl>
#> 1 Boucle du Mouhoun 96.9
#> 2 Cascades 63.6
#> 3 Centre 34.7
#> 4 Centre-Est 58.5
#> 5 Centre-Nord 94.9
#> 6 Centre-Ouest 32.4
#> 7 Centre-Sud 31.9
#> 8 Est 140.
#> 9 Hauts-Bassins 57.7
#> 10 Nord 155.
#> 11 Plateau-Central 55.9
#> 12 Sahel 145.
#> 13 Sud-Ouest 63.1
# Neyman allocation minimizes variance for fixed sample size
sampling_design() |>
stratify_by(region, alloc = "neyman", variance = bfa_eas_variance) |>
draw(n = 200) |>
execute(bfa_eas, seed = 2)
#> # A tbl_sample: 200 × 17
#> # Weights: 74.67 [52.65, 123]
#> ea_id region province commune urban_rural population households area_km2
#> * <chr> <fct> <fct> <fct> <fct> <dbl> <int> <dbl>
#> 1 EA_06470 Boucle … Mouhoun Kona Rural 1083 150 50.1
#> 2 EA_08656 Boucle … Kossi Nouna Rural 1197 177 45.9
#> 3 EA_08720 Boucle … Kossi Nouna Rural 1643 242 25.2
#> 4 EA_12444 Boucle … Banwa Solenzo Rural 1316 177 15.5
#> 5 EA_12420 Boucle … Banwa Solenzo Rural 79 11 5.68
#> 6 EA_06887 Boucle … Banwa Kouka Rural 1748 241 18.1
#> 7 EA_06014 Boucle … Sourou Kiemba… Rural 518 67 18.3
#> 8 EA_14033 Boucle … Nayala Yaba Rural 1115 147 11.8
#> 9 EA_07232 Boucle … Sourou Lankoue Rural 1031 136 18.5
#> 10 EA_04730 Boucle … Sourou Gomboro Rural 1597 225 43.8
#> # ℹ 190 more rows
#> # ℹ 9 more variables: accessible <lgl>, dist_road_km <dbl>,
#> # food_insecurity_pct <dbl>, cost <dbl>, .weight <dbl>, .sample_id <int>,
#> # .stage <int>, .weight_1 <dbl>, .fpc_1 <int>