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 99.2
#> 2 Cascades 57.7
#> 3 Centre 32.1
#> 4 Centre-Est 61.1
#> 5 Centre-Nord 97.4
#> 6 Centre-Ouest 33.7
#> 7 Centre-Sud 31.7
#> 8 Est 144.
#> 9 Hauts-Bassins 60.0
#> 10 Nord 137.
#> 11 Plateau-Central 59.4
#> 12 Sahel 142.
#> 13 Sud-Ouest 60.8
# 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 = 42)
#> # A tbl_sample: 200 × 17
#> # Weights: 74.5 [54.83, 121.6]
#> ea_id region province commune urban_rural population households area_km2
#> * <chr> <fct> <fct> <fct> <fct> <dbl> <int> <dbl>
#> 1 EA_02518 Boucle … Kossi Bouras… Rural 806 91 14.8
#> 2 EA_11697 Boucle … Banwa Sanaba Rural 1359 197 31.2
#> 3 EA_06821 Boucle … Nayala Kougny Rural 3371 449 3.12
#> 4 EA_12935 Boucle … Mouhoun Tcheri… Rural 1279 153 10.4
#> 5 EA_14276 Boucle … Nayala Ye Rural 1314 232 2.27
#> 6 EA_06814 Boucle … Nayala Kougny Rural 849 113 52.8
#> 7 EA_03727 Boucle … Kossi Dokui Rural 2183 349 10.0
#> 8 EA_02157 Boucle … Bale Boromo Rural 129 17 8.12
#> 9 EA_04881 Boucle … Nayala Gossina Rural 1549 250 15.1
#> 10 EA_05968 Boucle … Sourou Kiemba… Rural 976 155 20.4
#> # 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>