svybmi: Bourguignon (1999) multidimensional inequality indices...

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/svybmi.R

Description

Estimate indices from the Bourguignon (1999) class, a class of multidimensional inequality measures.

Usage

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svybmi(formula, design, ...)

## S3 method for class 'survey.design'
svybmi(
  formula,
  design,
  alpha = 0.5,
  beta = -2,
  dimw = NULL,
  na.rm = FALSE,
  ...
)

## S3 method for class 'svyrep.design'
svybmi(
  formula,
  design,
  alpha = 0.5,
  beta = -2,
  dimw = NULL,
  na.rm = FALSE,
  ...
)

## S3 method for class 'DBIsvydesign'
svybmi(formula, design, ...)

Arguments

formula

a formula specifying the variables. Variables can be numeric or ordered factors.

design

a design object of class survey.design or class svyrep.design from the survey library.

...

future expansion

alpha

a scalar defining the exponent of the indicator.

beta

a scalar defining the exponent of the indicator.

dimw

a vector defining the weight of each dimension in the multidimensional deprivation sum.

na.rm

Should cases with missing values be dropped?

Details

you must run the convey_prep function on your survey design object immediately after creating it with the svydesign or svrepdesign function.

Value

Object of class "cvystat", which are vectors with a "var" attribute giving the variance and a "statistic" attribute giving the name of the statistic.

Note

This function is experimental and is subject to change in later versions.

Author(s)

Guilherme Jacob, Djalma Pessoa and Anthony Damico

References

Francois Bourguignon (1999). Comment to 'Multidimensioned Approaches to Welfare Analysis' by Maasoumi, E. In: Handbook of income inequality measurement., ed. J. Silber, Boston, Dordrecht and London: Kluwer Academic, p. 477-484.

Maria Ana Lugo (2007). Comparing multidimensional indices of inequality: Methods and application. In: Research on Economic Inequality. Emerald, p. 213-236.

See Also

svyfgt

Examples

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library(survey)
library(laeken)
data(eusilc) ; names( eusilc ) <- tolower( names( eusilc ) )

# linearized design
des_eusilc <- svydesign( ids = ~rb030 , strata = ~db040 ,  weights = ~rb050 , data = eusilc )
des_eusilc <- convey_prep(des_eusilc)
des_eusilc <- update(des_eusilc, pb220a = ordered( pb220a ) )

# replicate-weighted design
des_eusilc_rep <- as.svrepdesign( des_eusilc , type = "bootstrap", replicates = 50 )
des_eusilc_rep <- convey_prep(des_eusilc_rep)

# linearized
svybmi(~eqincome+hy050n, design = des_eusilc, alpha = .5, beta = .5, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = des_eusilc, alpha = .5, beta = 0, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = des_eusilc, alpha = .5, beta = -.5, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = des_eusilc, alpha = .5, beta = -1, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = des_eusilc, alpha = .5, beta = -2, na.rm = FALSE )

# replicate
svybmi(~eqincome+hy050n, design = des_eusilc_rep, alpha = .5, beta = .5, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = des_eusilc_rep, alpha = .5, beta = 0, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = des_eusilc_rep, alpha = .5, beta = -.5, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = des_eusilc_rep, alpha = .5, beta = -1, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = des_eusilc_rep, alpha = .5, beta = -2, na.rm = FALSE )

## Not run: 

# database-backed design
library(RSQLite)
library(DBI)
dbfile <- tempfile()
conn <- dbConnect( RSQLite::SQLite() , dbfile )
dbWriteTable( conn , 'eusilc' , eusilc )

dbd_eusilc <-
	svydesign(
		ids = ~rb030 ,
		strata = ~db040 ,
		weights = ~rb050 ,
		data="eusilc",
		dbname=dbfile,
		dbtype="SQLite"
	)

dbd_eusilc <- convey_prep( dbd_eusilc )

# linearized
svybmi(~eqincome+hy050n, design = dbd_eusilc, alpha = .5, beta = .5, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = dbd_eusilc, alpha = .5, beta = 0, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = dbd_eusilc, alpha = .5, beta = -.5, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = dbd_eusilc, alpha = .5, beta = -1, na.rm = FALSE )
svybmi(~eqincome+hy050n, design = dbd_eusilc, alpha = .5, beta = -2, na.rm = FALSE )

# subsetting:
sub_dbd_eusilc <- subset( dbd_eusilc, db040 == "Styria")
svybmi(~eqincome+hy050n, design = sub_dbd_eusilc, alpha = .5, beta = .5, na.rm = FALSE )

dbRemoveTable( conn , 'eusilc' )

dbDisconnect( conn , shutdown = TRUE )


## End(Not run)

convey documentation built on July 1, 2020, 11:44 p.m.