Calculate CMAM performance indicators
Arguments
- .data
A data.frame containing programme monitoring data on number of cured, deaths, defaulters and non-response. The required data.frame holds rows of data corresponding to total counts for each performance indicator (i.e., cured, dead, defaulter and non-responder) rather than rows of individual cases.
- vars
A vector of variable names specifying cured, dead, defaulter and non-responder (in this specific order) values in
.data. If NULL (default), typical names used for these variables will be searched and used accordingly. If search doesn't yield matching variable names, the first 4 columns of the data.frame will be used.- add
Logical. Should result be added to
.data. Default is TRUE.
Examples
calculate_performance(.data = monitoring)
#> # A tibble: 8,234 × 20
#> State Locality `Beginning Of Month` `New Admissions` Male Female Cured Death
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Gaze… El Qura… 16 16 8 8 23 0
#> 2 Gaze… El Qura… 56 24 11 13 0 0
#> 3 Gaze… El Qura… 80 41 16 25 22 0
#> 4 Gaze… El Qura… 81 43 21 22 29 0
#> 5 Gaze… El Qura… 93 51 31 30 36 2
#> 6 Gaze… El Qura… 103 59 34 25 3 0
#> 7 Gaze… El Qura… 163 69 34 35 8 0
#> 8 Gaze… El Qura… 104 108 56 40 6 0
#> 9 Gaze… El Qura… 275 123 61 62 111 0
#> 10 Gaze… El Qura… 204 81 39 40 52 0
#> # ℹ 8,224 more rows
#> # ℹ 12 more variables: Default <dbl>, `Non-Responder` <dbl>,
#> # `Total Discharge` <dbl>, `Rutf Consumed` <dbl>, Screening <dbl>,
#> # Sites <lgl>, Month <chr>, Year <chr>, cured_prop <dbl>, dead_prop <dbl>,
#> # defaulter_prop <dbl>, nr_prop <dbl>