vardpoor (version 0.3.4)

linrmi: Linearization of the relative median income ratio

Description

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

Usage

linrmi(Y, id, age,
  weight = NULL,
  sort = NULL,
  Dom = NULL,
  period = NULL,
  dataset = NULL,
  order_quant = 50,
  var_name = "lin_rmi")

Arguments

Y

Study variable (for example equalized disposable income). One dimensional object convertible to one-column data.frame or variable name as character, column number or logical vector with only one TRUE value (length of the vector h

id

Optional variable for unit ID codes. One dimensional object convertible to one-column data.frame or variable name as character, column number or logical vector with only one TRUE value (length of the vector has to be the same as

weight

Optional weight variable. One dimensional object convertible to one-column data.frame or variable name as character, column number or logical vector with only one TRUE value (length of the vector has to be the same as the column

age

Age variable. One dimensional object convertible to one-column data.frame or variable name as character, column number or logical vector with only one TRUE value (length of the vector has to be the same as the column count of

sort

Optional variable to be used as tie-breaker for sorting. One dimensional object convertible to one-column data.frame or variable name as character, column number or logical vector with only one TRUE value (length of the vector ha

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.frame or variable names as character vector, column numbers as numeric vec

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.frame or variable names as character, column numbers as numeric vector or logical vecto

dataset

Optional survey data object convertible to data.frame.

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 at-risk-of-poverty threshold equal to some percentage of me

var_name

A character specifying the name of the linearized variable.

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 http://www5.statcan.gc.ca/bsolc/olc-cel/olc-cel?lang=eng&catno=12-001-X19990024882.

See Also

varpoord , vardcrospoor, vardchangespoor

Examples

data(eusilc)

dati <- data.frame(IDd = 1:nrow(eusilc), eusilc)

# Full population
d <- linrmi(Y="eqIncome", id="IDd",  age="age", weight="rb050", 
                  Dom=NULL, dataset=dati, order_quant=50)
d$value

# By domains
dd <- linrmi(Y="eqIncome", id="IDd", age="age", weight="rb050", 
                     Dom="db040", dataset=dati, percentage=60, order_quant=50)

dd