phe_quantile {PHEindicatormethods}

Assign Quantiles using phe_quantile

Description

Assigns data to quantiles based on numeric data rankings.

Usage

phe_quantile(
  data,
  values,
  nquantiles = 10L,
  invert = TRUE,
  inverttype = "logical",
  type = "full"
)

Arguments

data

a data frame containing the quantitative data to be assigned to quantiles. If pre-grouped, separate sets of quantiles will be assigned for each grouping set; unquoted string; no default

values

field name from data containing the numeric values to rank data by and assign quantiles from; unquoted string; no default

nquantiles

the number of quantiles to separate each grouping set into; numeric; default=10L

invert

whether the quantiles should be directly (FALSE) or inversely (TRUE) related to the numerical value order; logical (to apply same value to all grouping sets) OR unquoted string referencing field name from data that stores logical values for each grouping set; default = TRUE (ie highest values assigned to quantile 1)

inverttype

whether the invert argument has been specified as a logical value or a field name from data; quoted string "field" or "logical"; default = "logical"

type

defines whether to include metadata columns in output to reference the arguments passed; can be "standard" or "full"; quoted string; default = "full"

Value

When type = "full", returns the original data.frame with quantile (quantile value), nquantiles (number of quantiles requested), groupvars (grouping sets quantiles assigned within) and invert (indicating direction of quantile assignment) fields appended.

Notes

See OHID Technical Guide - Assigning Deprivation Categories for methodology. In particular, note that this function strictly applies the algorithm defined but some manual review, and potentially adjustment, is advised in some cases where multiple small areas with equal rank fall across a natural quantile boundary.

See Also

Other PHEindicatormethods package functions: assign_funnel_significance(), calculate_ISRate(), calculate_ISRatio(), calculate_funnel_limits(), calculate_funnel_points(), phe_dsr(), phe_life_expectancy(), phe_mean(), phe_proportion(), phe_rate(), phe_sii()

Examples

df <- data.frame(
  region    = as.character(rep(c("Region1","Region2","Region3","Region4"),
                               each=250)),
  smallarea = as.character(paste0("Area",seq_along(1:1000))),
  vals      = as.numeric(sample(200, 1000, replace = TRUE)),
  stringsAsFactors = FALSE)

# assign small areas to deciles across whole data frame
phe_quantile(df, vals)

# assign small areas to deciles within regions by pre-grouping the data frame
library(dplyr)
df_grp <- df %>% group_by(region)
phe_quantile(df_grp, vals)

# assign small areas to quintiles, where highest value = highest quantile
phe_quantile(df, vals, nquantiles = 5L, invert=FALSE)