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Helper function for the estimation of stratified quantiles

Source: R/estimate_proportion.R
strata_normal_quantile.Rd

[Stable]

This function wraps the estimation of stratified percentiles when we assume the approximation for large numbers. This is necessary only in the case proportions for each strata are unequal.

Usage 

strata_normal_quantile(vars, weights, conf_level)

Arguments

vars

(character)
variable names for the primary analysis variable to be iterated over.

weights

(numeric or NULL)
weights for each level of the strata. If NULL, they are estimated using the iterative algorithm proposed in Yan and Su (2010) that minimizes the weighted squared length of the confidence interval.

conf_level

(proportion)
confidence level of the interval.

Value

Stratified quantile.

See also

prop_strat_wilson()

Examples 

strata_data <- table(data.frame(
  "f1" = sample(c(TRUE, FALSE), 100, TRUE),
  "f2" = sample(c("x", "y", "z"), 100, TRUE),
  stringsAsFactors = TRUE
))
ns <- colSums(strata_data)
ests <- strata_data["TRUE", ] / ns
vars <- ests * (1 - ests) / ns
weights <- rep(1 / length(ns), length(ns))

strata_normal_quantile(vars, weights, 0.95)
#> [1] 1.14181