ccwrap: Wrapper for cross-classified data that standardises rates...

In DasGuptR: Das Gupta Standardisation and Decomposition

Wrapper for cross-classified data that standardises rates across a pair of populations. Because these are (r+r')/2 * Q(a_i), this requires 1) doing the rate standardisation on each sub-population, 2) performing the standardisation on the cross classified structure variables, 3) multiplying and (optionally) aggregating up

Description

Wrapper for cross-classified data that standardises rates across a pair of populations. Because these are (r+r')/2 * Q(a_i), this requires 1) doing the rate standardisation on each sub-population, 2) performing the standardisation on the cross classified structure variables, 3) multiplying and (optionally) aggregating up

Usage

ccwrap(
  pw,
  pop,
  factors,
  id_vars,
  crossclassified,
  agg,
  ratefunction = NULL,
  quietly = TRUE
)

Arguments

pw	dataframe containing two populations worth of factor data, with columns specifying 1) population and 2) each rate-factor to be considered. must have column named "pop" indicating the population ID.
pop	name (character string) of variable indicating population
factors	names (character vector) of variables indicating compositional factors
id_vars	character vector of variables indicating sub-populations
crossclassified	character string of variable indicating size of sub-population. If specified, the proportion of each population in a given sub-population (e.g. each age-sex combination) is re-expressed as a product of symmetrical expressions representing the different variables (age, sex) constituting the sub-populations.
agg	logical indicating whether, when cross-classified data is used, to output should be aggregated up to the population level
ratefunction	user defined character string in R syntax that when evaluated specifies the function defining the rate as a function of factors. if NULL then will assume rate is the product of all factors.
quietly	logical indicating whether interim messages should be outputted indicating progress through the P factors

Value

data.frame that includes K-a standardised rates for each population and each factor a, along with differences between standardised rates

DasGuptR documentation built on April 11, 2025, 5:56 p.m.