Estimate the relative median at-risk-of-poverty gap, which is defined as the relative difference between the median equivalized disposable income of persons below the at-risk-of-poverty threshold and the at-risk-of-poverty threshold itself (expressed as a percentage of the at-risk-of-poverty threshold).
rmpg(
inc,
weights = NULL,
sort = NULL,
years = NULL,
breakdown = NULL,
design = NULL,
cluster = NULL,
data = NULL,
var = NULL,
alpha = 0.05,
na.rm = FALSE,
...
)A list of class "rmpg" (which inherits from the class
"indicator") with the following components:
a numeric vector containing the overall value(s).
a data.frame containing the values by
domain, or NULL.
a character string specifying the type of variance
estimation used, or NULL if variance estimation was omitted.
a numeric vector containing the variance estimate(s), or
NULL.
a data.frame containing the variance
estimates by domain, or NULL.
a numeric vector or matrix containing the lower and upper
endpoints of the confidence interval(s), or NULL.
a data.frame containing the lower and upper
endpoints of the confidence intervals by domain, or NULL.
a numeric value giving the significance level used for
computing the confidence interval(s) (i.e., the confidence level is \(1 -
\)alpha), or NULL.
a numeric vector containing the different years of the survey.
a character vector containing the different domains of the breakdown.
a numeric vector containing the at-risk-of-poverty threshold(s).
either a numeric vector giving the equivalized disposable income,
or (if data is not NULL) a character string, an integer or a
logical vector specifying the corresponding column of data.
optional; either a numeric vector giving the personal sample
weights, or (if data is not NULL) a character string, an
integer or a logical vector specifying the corresponding column of
data.
optional; either a numeric vector giving the personal IDs to be
used as tie-breakers for sorting, or (if data is not NULL) a
character string, an integer or a logical vector specifying the corresponding
column of data.
optional; either a numeric vector giving the different years of
the survey, or (if data is not NULL) a character string, an
integer or a logical vector specifying the corresponding column of
data. If supplied, values are computed for each year.
optional; either a numeric vector giving different domains,
or (if data is not NULL) a character string, an integer or a
logical vector specifying the corresponding column of data. If
supplied, the values for each domain are computed in addition to the overall
value. Note that the same (overall) threshold is used for all domains.
optional and only used if var is not NULL; either
an integer vector or factor giving different strata for stratified sampling
designs, or (if data is not NULL) a character string, an
integer or a logical vector specifying the corresponding column of
data.
optional and only used if var is not NULL;
either an integer vector or factor giving different clusters for cluster
sampling designs, or (if data is not NULL) a character string,
an integer or a logical vector specifying the corresponding column of
data.
an optional data.frame.
a character string specifying the type of variance estimation to
be used, or NULL to omit variance estimation. See
variance for possible values.
numeric; if var is not NULL, this gives the
significance level to be used for computing the confidence interval (i.e.,
the confidence level is \(1 - \)alpha).
a logical indicating whether missing values should be removed.
if var is not NULL, additional arguments to be
passed to variance.
Andreas Alfons
The implementation strictly follows the Eurostat definition.
A. Alfons and M. Templ (2013) Estimation of Social Exclusion Indicators from Complex Surveys: The R Package laeken. Journal of Statistical Software, 54(15), 1--25. tools:::Rd_expr_doi("10.18637/jss.v054.i15")
Working group on Statistics on Income and Living Conditions (2004) Common cross-sectional EU indicators based on EU-SILC; the gender pay gap. EU-SILC 131-rev/04, Eurostat, Luxembourg.
arpt, variance
data(eusilc)
# overall value
rmpg("eqIncome", weights = "rb050", data = eusilc)
# values by region
rmpg("eqIncome", weights = "rb050",
breakdown = "db040", data = eusilc)
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