internal function to calculate proportion estimations

Usage

create_prop_internal(
  var,
  domains = NULL,
  subpop = NULL,
  disenio,
  ci = FALSE,
  deff = FALSE,
  ess = FALSE,
  ajuste_ene = FALSE,
  rel_error = FALSE,
  log_cv = FALSE,
  unweighted = FALSE,
  standard_eval = TRUE,
  rm.na = FALSE,
  env = parent.frame(),
  ci_logit = FALSE
)

Arguments

var: integer dummy variable within the dataframe
domains: domains to be estimated separated by the + character.
subpop: integer dummy variable to filter the dataframe
disenio: complex design created by survey package
ci: boolean indicating if the confidence intervals must be calculated
deff: boolean Design effect
ess: boolean Effective sample size
ajuste_ene: boolean indicating if an adjustment for the sampling-frame transition period must be used
rel_error: boolean Relative error
log_cv: boolean indicating if the log cv must be returned
unweighted: boolean Add non weighted count if it is required
standard_eval: boolean indicating if the function is inside another function, by default it is TRUE, avoid problems with lazy eval.
rm.na: boolean indicating if NA values must be removed
env: parent environment to get some variables
ci_logit: boolean indicating if interval confidence is logit

Value

dataframe that contains the inputs and all domains to be evaluated