Create the inputs to evaluate the quality of total estimations

create_size generates a dataframe with the following elements: sum, degrees of freedom, sample size, and coefficient of variation. The function allows grouping in several domains.

Usage

create_size(
  var,
  domains = NULL,
  subpop = NULL,
  design,
  ci = FALSE,
  ess = FALSE,
  ajuste_ene = FALSE,
  standard_eval = FALSE,
  rm.na = FALSE,
  deff = FALSE,
  rel_error = FALSE,
  unweighted = FALSE,
  df_type = c("chile", "eclac"),
  eclac_input = FALSE
)

Arguments

var: numeric variable within the dataframe. When the domain parameter is not used, it is possible to include more than one variable using the + separator. When a value is introduced in the domain parameter, the estimation variable must be a dummy variable.
domains: domains to be estimated separated by the + character.
subpop: integer dummy variable to filter the dataframe.
design: complex design created by survey package.
ci: boolean indicating if the confidence intervals must be calculated.
ess: boolean effective sample size.
ajuste_ene: boolean indicating if an adjustment for the sampling-frame transition period must be used.
standard_eval: boolean indicating if the function is wrapped inside another function, if TRUE avoid lazy eval errors.
rm.na: boolean remove NA values if required.
deff: boolean design effect.
rel_error: boolean relative error.
unweighted: boolean add non-weighted count if required.
df_type: character use degrees of freedom calculation approach from INE Chile or CEPAL. Options are "chile" or "eclac".
eclac_input: boolean return eclac inputs

Value

dataframe that contains the inputs and all domains to be evaluated.

Examples

dc <- survey::svydesign(ids = ~varunit, strata = ~varstrat, data = epf_personas, weights = ~fe)
create_size("ocupado", "zona+sexo", design = dc)
#>   zona sexo      stat        se  df    n         cv
#> 1    1    1 1652700.9 124118.08 127 6651 0.07510015
#> 2    2    1 1239916.7  83403.85 121 5513 0.06726568
#> 3    1    2 1388475.0 104249.82 127 5638 0.07508225
#> 4    2    2  987159.5  63514.46 121 4787 0.06434063