convey (version 0.2.2)

svywatts: Watts poverty index (EXPERIMENTAL)

Description

Estimate the Watts (1968) poverty measure

Usage

svywatts(formula, design, ...)
# S3 method for survey.design
svywatts(
  formula,
  design,
  type_thresh = "abs",
  abs_thresh = NULL,
  percent = 0.6,
  quantiles = 0.5,
  na.rm = FALSE,
  thresh = FALSE,
  ...
)
# S3 method for svyrep.design
svywatts(
  formula,
  design,
  type_thresh = "abs",
  abs_thresh = NULL,
  percent = 0.6,
  quantiles = 0.5,
  na.rm = FALSE,
  thresh = FALSE,
  ...
)
# S3 method for DBIsvydesign
svywatts(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.

...

passed to svyarpr and svyarpt

type_thresh

type of poverty threshold. If "abs" the threshold is fixed and given the value of abs_thresh; if "relq" it is given by percent times the quantile; if "relm" it is percent times the mean.

abs_thresh

poverty threshold value if type_thresh is "abs"

percent

the multiple of the the quantile or mean used in the poverty threshold definition

quantiles

the quantile used used in the poverty threshold definition

na.rm

Should cases with missing values be dropped?

thresh

return the poverty threshold value

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

Harold W. Watts (1968). An economic definition of poverty. Institute For Research on Poverty Discussion Papers, n.5. University of Wisconsin. URL https://www.irp.wisc.edu/publications/dps/pdfs/dp568.pdf.

Guillaume Osier (2009). Variance estimation for complex indicators of poverty and inequality. Journal of the European Survey Research Association, Vol.3, No.3, pp. 167-195, ISSN 1864-3361, URL http://ojs.ub.uni-konstanz.de/srm/article/view/369.

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

svyarpt

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 )

# absolute poverty threshold
svywatts(~eqincome, des_eusilc, abs_thresh=10000)
# poverty threshold equal to arpt
svywatts(~eqincome, des_eusilc, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svywatts(~eqincome, des_eusilc, type_thresh= "relm" , thresh = TRUE)

#  using svrep.design:
# absolute poverty threshold
svywatts(~eqincome, des_eusilc_rep, abs_thresh=10000)
# poverty threshold equal to arpt
svywatts(~eqincome, des_eusilc_rep, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svywatts(~eqincome, des_eusilc_rep, type_thresh= "relm" , thresh = TRUE)

# }
# 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 )

# absolute poverty threshold
svywatts(~eqincome, dbd_eusilc, abs_thresh=10000)
# poverty threshold equal to arpt
svywatts(~eqincome, dbd_eusilc, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svywatts(~eqincome, dbd_eusilc, type_thresh= "relm" , thresh = TRUE)

dbRemoveTable( conn , 'eusilc' )

dbDisconnect( conn , shutdown = TRUE )

# }
# NOT RUN {
# }