convey (version 0.2.2)

svysst: Sen-Shorrocks-Thon poverty index (EXPERIMENTAL)

Description

Estimate the Sen-Shorrocks-Thon poverty measure.

Usage

svysst(formula, design, ...)
# S3 method for survey.design
svysst(
  formula,
  design,
  abs_thresh = NULL,
  na.rm = FALSE,
  components = FALSE,
  ...
)
# S3 method for svyrep.design
svysst(
  formula,
  design,
  abs_thresh = NULL,
  na.rm = FALSE,
  components = FALSE,
  ...
)
# S3 method for DBIsvydesign
svysst(formula, design, ...)

Arguments

formula

a formula specifying the income variable

design

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

...

future expansion

abs_thresh

poverty threshold value

na.rm

Should cases with missing values be dropped?

components

Keep estimates of FGT(0), FGT(1), Gini index of poverty gap ratios.

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.

Details

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

References

Anthony F. Shorrocks (1995). Revisiting the Sen Poverty Index. Econometrica, v. 63, n. 5, pp. 1225-230. URL http://www.jstor.org/stable/2171728.

Dominique Thon (1979). On measuring poverty. Review of Income and Wealth, v. 25, n. 4, pp. 429-439. URL http://dx.doi.org/10.1111/j.1475-4991.1979.tb00117.x.

Amartya K. Sen (1976). Poverty: An Ordinal Approach to Measurement. Econometrica, v. 44, n. 3, pp. 219-231. URL http://www.jstor.org/stable/1912718.

See Also

svysen, svyfgt, svygini.

Examples

# NOT RUN {
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 )

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

# using linearized design
svysst( ~eqincome, des_eusilc, abs_thresh=10000 )

# using replicate design:
svysst( ~eqincome, des_eusilc_rep, abs_thresh = 10000 )


# }
# 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 SE:
svysst(~eqincome, dbd_eusilc, abs_thresh=10000)

dbRemoveTable( conn , 'eusilc' )

dbDisconnect( conn , shutdown = TRUE )

# }
# NOT RUN {
# }