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Data was generated through a community-based sentinel site conducted across three provinces. Each province's dataset presents distinct data quality scenarios, requiring tailored prevalence analysis:

  • "Province 1" has MFAZ's standard deviation and age ratio test rating of acceptability falling within range;

  • "Province 2" has age ratio rated as problematic but with an acceptable standard deviation of MFAZ;

  • "Province 3" has both tests rated as problematic.

This sample data is useful to demonstrate the use of prevalence functions on a multi-area survey data where variations in the rating of acceptability of the standard deviation exist, hence require different analyses approaches for each area to ensure accurate estimation.

Usage

anthro.04

Format

A tibble of 3,002 x 8.

VariableDescription
provincelocation where data was collected
clusterPrimary sampling unit
sexSex, "m" = boys, "f" = girls
agecalculated age in months with two decimal places
muacMid-upper arm circumference (mm)
edemaEdema, "n" = no, "y" = yes
mfazMUAC-for-age z-scores with 3 decimal places
flag_mfazFlagged observations. 1=flagged, 0=not flagged

Source

Anonymous

Examples

anthro.04
#> # A tibble: 3,002 × 8
#>    province   cluster   sex   age  muac edema   mfaz flag_mfaz
#>    <chr>        <int> <dbl> <int> <dbl> <chr>  <dbl>     <dbl>
#>  1 Province 1     298     2    24   136 n     -1.12          0
#>  2 Province 1     298     2    30   116 n     -3.44          0
#>  3 Province 1     298     2     7   140 n      0.084         0
#>  4 Province 1     298     2    18   144 n     -0.068         0
#>  5 Province 1     298     2    10   125 n     -1.48          0
#>  6 Province 1     298     2    11   125 n     -1.52          0
#>  7 Province 1     298     2    30   136 n     -1.46          0
#>  8 Province 1     298     2    24   133 n     -1.40          0
#>  9 Province 1     298     2    10   122 n     -1.78          0
#> 10 Province 1     298     2    24   142 n     -0.579         0
#> # ℹ 2,992 more rows