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Estimate all standard RAM-OP indicators

Source: R/06-estimate_op.R
estimate_op.Rd

Estimate all standard RAM-OP indicators

Usage

estimate_op(
  x,
  w,
  indicators = c("demo", "anthro", "food", "hunger", "adl", "disability", "mental",
    "dementia", "health", "oedema", "screening", "income", "wash", "visual", "misc"),
  replicates = 399
)

Arguments

x

Indicators dataset produced by create_op() with primary sampling unit (PSU) in column named "psu"`

w

A data frame with primary sampling unit (PSU) in column named "psu" and survey weight (i.e. PSU population) in column named "pop".

indicators

A character vector of indicator set names to estimate. Indicator set names are "demo", "anthro", "food", "hunger", "disability", "adl", "mental", "dementia", "health", "income", "wash", "visual", and "misc". Default is all indicator sets.

replicates

Number of bootstrap replicates. Default is 399.

Value

A tibble::tibble() of boot estimates for all specified standard RAM-OP indicators.

Examples

estimate_op(x = create_op(testSVY), w = testPSU, replicates = 9)
#> ℹ Checking if demo, food, hunger, disability, adl, mental, dementia, health, income, wash, anthro, oedema, screening, visual, misc are RAM-OP indicators
#> ✔ All of `indicators` are RAM-OP indicators
#> ✔ x has the appropriate/expected data structure
#> ✔ x has the appropriate/expected data structure
#> ✔ x has the appropriate/expected data structure
#> ✔ x has the appropriate/expected data structure
#> ✔ x has the appropriate/expected data structure
#> ✔ x has the appropriate/expected data structure
#> ✔ x has the appropriate/expected data structure
#> ✔ x has the appropriate/expected data structure
#> ✔ x has the appropriate/expected data structure
#> # A tibble: 139 × 13
#>    INDICATOR GROUP       LABEL TYPE  EST.ALL LCL.ALL UCL.ALL EST.MALES LCL.MALES
#>    <fct>     <fct>       <fct> <fct>   <dbl>   <dbl>   <dbl>     <dbl>     <dbl>
#>  1 resp1     Survey      Resp… Prop…   87.0   81.5     91.7      84        75.8 
#>  2 resp2     Survey      Resp… Prop…    7.81   5.83    10.9       7.89      2.48
#>  3 resp3     Survey      Resp… Prop…    3.65   0.729    6.67      6.33      1.55
#>  4 resp4     Survey      Resp… Prop…    1.04   0        2.08      1.27      0   
#>  5 age       Demography… Mean… Mean    70.2   69.0     71.7      70.2      69.1 
#>  6 ageGrp1   Demography… Self… Prop…    0      0        0         0         0   
#>  7 ageGrp2   Demography… Self… Prop…   54.2   48.0     62.2      50        39.6 
#>  8 ageGrp3   Demography… Self… Prop…   22.4   19.5     33.3      27.1      17.2 
#>  9 ageGrp4   Demography… Self… Prop…   18.8   11.5     26.1      18.4       6.86
#> 10 ageGrp5   Demography… Self… Prop…    2.08   0.729    4.06      5.33      1.46
#> # ℹ 129 more rows
#> # ℹ 4 more variables: UCL.MALES <dbl>, EST.FEMALES <dbl>, LCL.FEMALES <dbl>,
#> #   UCL.FEMALES <dbl>