Description Usage Arguments Details Value Note Author(s) References See Also Examples
Estimate the Zenga index, a measure of inequality
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formula |
a formula specifying the income variable. |
design |
a design object of class |
... |
future expansion |
na.rm |
Should cases with missing values be dropped? |
you must run the convey_prep
function on your survey design object immediately after creating it with the svydesign
or svrepdesign
function.
Object of class "cvystat
", which are vectors with a "var
" attribute giving the variance and a "statistic
" attribute giving the name of the statistic.
This function is experimental and is subject to changes in later versions.
Guilherme Jacob, Djalma Pessoa and Anthony Damico
Lucio Barabesi, Giancarlo Diana and Pier Francesco Perri (2016). Linearization of inequality indexes in the design-based framework. Statistics. URL http://www.tandfonline.com/doi/pdf/10.1080/02331888.2015.1135924.
Matti Langel (2012). Measuring inequality in finite population sampling. PhD thesis: Universite de Neuchatel, URL https://doc.rero.ch/record/29204/files/00002252.pdf.
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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)
# replicate-weighted design
des_eusilc_rep <- as.svrepdesign( des_eusilc , type = "bootstrap" )
des_eusilc_rep <- convey_prep(des_eusilc_rep)
# variable without missing values
svyzenga(~eqincome, des_eusilc)
svyzenga(~eqincome, des_eusilc_rep)
# subsetting:
svyzenga(~eqincome, subset( des_eusilc, db040 == "Styria"))
svyzenga(~eqincome, subset( des_eusilc_rep, db040 == "Styria"))
## Not run:
# variable with with missings
svyzenga(~py010n, des_eusilc )
svyzenga(~py010n, des_eusilc_rep )
svyzenga(~py010n, des_eusilc, na.rm = TRUE )
svyzenga(~py010n, des_eusilc_rep, na.rm = TRUE )
# 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 )
# variable without missing values
svyzenga(~eqincome, dbd_eusilc)
# subsetting:
svyzenga(~eqincome, subset( dbd_eusilc, db040 == "Styria"))
# variable with with missings
svyzenga(~py010n, dbd_eusilc )
svyzenga(~py010n, dbd_eusilc, na.rm = TRUE )
dbRemoveTable( conn , 'eusilc' )
dbDisconnect( conn , shutdown = TRUE )
## End(Not run)
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