anthro.03 contains survey data of four districts. Each district data set
presents distinct data quality scenarios that requires tailored prevalence
analysis approach: two districts show a problematic WFHZ standard deviation
whilst the remaining are all within range.
This sample data is useful to demonstrate the use of the prevalence functions on a multiple-area survey data where there can be variations in the rating of acceptability of the standard deviation, hence require different analyses approaches for each area to ensure accurate estimation.
Format
A tibble of 943 x 9.
| Variable | Description |
| district | The location where data was collected |
| cluster | Primary sampling unit |
| team | Survey teams |
| sex | Sex, "m" = boys, "f" = girls |
| age | calculated age in months with two decimal places |
| weight | Weight (kg) |
| height | Height (cm) |
| edema | Edema, "n" = no, "y" = yes |
| muac | Mid-upper arm circumference (mm) |
Examples
anthro.03
#> # A tibble: 943 × 9
#> district cluster team sex age weight height edema muac
#> <chr> <int> <int> <chr> <dbl> <dbl> <dbl> <chr> <int>
#> 1 Metuge 2 2 m 9.99 10.1 69.3 n 172
#> 2 Metuge 2 2 f 43.6 10.9 91.5 n 130
#> 3 Metuge 2 2 f 32.8 11.4 91.4 n 153
#> 4 Metuge 2 2 f 7.62 8.3 69.5 n 133
#> 5 Metuge 2 2 m 28.4 10.7 82.3 n 143
#> 6 Metuge 2 2 f 12.3 6.6 69.4 n 121
#> 7 Metuge 2 2 f 32.0 11.1 85.2 n 148
#> 8 Metuge 2 2 m 34.9 12.6 86.5 n 156
#> 9 Metuge 3 3 m 9.07 8.3 71.4 n 145
#> 10 Metuge 3 3 m 45.5 11.5 85.7 n 145
#> # ℹ 933 more rows