vardpoor (version 0.20.1)

linrmir: Linearization of the relative median income ratio

Description

Estimates the relative median income ratio (defined as the ratio of the median equivalised disposable income of people aged above age to the median equivalised disposable income of those aged below 65) and computes linearized variable for variance estimation.

Usage

linrmir(
  Y,
  id = NULL,
  age,
  weight = NULL,
  sort = NULL,
  Dom = NULL,
  period = NULL,
  dataset = NULL,
  order_quant = 50,
  var_name = "lin_rmir",
  checking = TRUE
)

Arguments

Y

Study variable (for example equalized disposable income). One dimensional object convertible to one-column data.table or variable name as character, column number.

id

Optional variable for unit ID codes. One dimensional object convertible to one-column data.table or variable name as character, column number.

age

Age variable. One dimensional object convertible to one-column data.table or variable name as character, column number.

weight

Optional weight variable. One dimensional object convertible to one-column data.table or variable name as character, column number.

sort

Optional variable to be used as tie-breaker for sorting. One dimensional object convertible to one-column data.table or variable name as character, column number.

Dom

Optional variables used to define population domains. If supplied, linearization of at-risk-of-poverty threshold is done for each domain. An object convertible to data.table or variable names as character vector, column numbers as numeric vector.

period

Optional variable for survey period. If supplied, linearization of at-risk-of-poverty threshold is done for each survey period. Object convertible to data.table or variable names as character, column numbers as numeric vector.

dataset

Optional survey data object convertible to data.table.

order_quant

A numeric value in range \(\left[ 0,100 \right]\) for \(\alpha\) in the formula for at-risk-of-poverty threshold computation: $$\frac{p}{100} \cdot Z_{\frac{\alpha}{100}}.$$ For example, to compute the relative median income ratio to some percentage of median income, \(\alpha\) should be set equal to 50.

var_name

A character specifying the name of the linearized variable.

checking

Optional variable if this variable is TRUE, then function checks data preparation errors, otherwise not checked. This variable by default is TRUE.

Value

A list with four objects are returned:

• value - a data.table containing the estimated relative median income ratio.

• lin - a data.table containing the linearized variables of the relative median income ratio.

Details

The implementation strictly follows the Eurostat definition.

References

Working group on Statistics on Income and Living Conditions (2015) Task 5 - Improvement and optimization of calculation of net change. LC- 139/15/EN, Eurostat. Jean-Claude Deville (1999). Variance estimation for complex statistics and estimators: linearization and residual techniques. Survey Methodology, 25, 193-203, URL https://www150.statcan.gc.ca/n1/pub/12-001-x/1999002/article/4882-eng.pdf.

See Also

varpoord, vardcrospoor, vardchangespoor

Examples

# NOT RUN {
library("laeken")
library("data.table")
data("eusilc")
dataset1 <- data.table(IDd = paste0("V", 1 : nrow(eusilc)), eusilc)
 
# Full population
d <- linrmir(Y = "eqIncome", id = "IDd",  age = "age",
             weight = "rb050", Dom = NULL,  
             dataset = dataset1, order_quant = 50L)
 
# }
# NOT RUN {
 # By domains
 dd <- linrmir(Y = "eqIncome", id = "IDd", age = "age",
               weight = "rb050", Dom = "db040",
               dataset = dataset1, order_quant = 50L)
 dd
# }
# NOT RUN {
# }