Compute Percentile Ratios

This function calculates the ratio between two percentiles (e.g., P90/P10) for each dataset in a list.

Usage

run_weighted_ratios(
  data_list,
  var_name,
  wgt_name = NULL,
  upper_percentile,
  lower_percentile,
  type = c("type_4", "type_2"),
  na.rm = TRUE
)

Arguments

data_list

A named list of data frames.

var_name

A string. The name of the variable to analyze (e.g., "dhi", "income").

wgt_name

A string (optional). The name of the weight variable. If NULL, equal weights are assumed.

upper_percentile

A numeric scalar (between 0 and 1). The higher percentile (e.g., 0.9).

lower_percentile

A numeric scalar (between 0 and 1). The lower percentile (e.g., 0.1).

type

A character string indicating the percentile type used in compute_weighted_percentiles. Defaults to "type_4".

na.rm

Logical. Should missing values be removed before computation? Default is TRUE.

Value

A named list. Each element is named by country and contains a named numeric vector, where names are years and values are the percentile ratios.

Details

If upper_percentile is less than lower_percentile, the values are automatically swapped and a warning is issued.

Examples

if (FALSE) { # \dontrun{
library(lissyrtools)
library(purrr)
library(dplyr)

datasets <- lissyrtools::lissyuse(data = c("de", "es", "uk"), vars = c("dhi"), from = 2016)

datasets <- datasets %>% 
 map(~ .x %>% filter(!is.na(dhi))) %>%
 map(~ .x %>% mutate(new_wgt = hwgt * nhhmem)) %>%
 apply_iqr_top_bottom_coding("dhi", "hwgt", type = "type_2") %>%
 apply_sqrt_equivalisation("dhi")


# Compute dhi  ratios

p90_p10 <- run_weighted_ratios(datasets, var_name = "dhi", wgt_name = "hwgt", 
                                upper_percentile = 0.9, lower_percentile = 0.1)
                                
p90_p50 <- run_weighted_ratios(datasets, var_name = "dhi", wgt_name = "hwgt", 
                                upper_percentile = 0.9, lower_percentile = 0.5) 
                                                                
p80_p20 <- run_weighted_ratios(datasets, var_name = "dhi", wgt_name = "hwgt", 
                                upper_percentile = 0.8, lower_percentile = 0.2) 
print(p90_p10)
print(p90_p50) 
print(p80_p20)
} # }