Estimate the quintile share ratio, which is defined as the ratio of the sum of equivalized disposable income received by the top 20% to the sum of equivalized disposable income received by the bottom 20%.
qsr(
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 "qsr"
(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.
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.
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.
incQuintile
, variance
,
gini
data(eusilc)
# overall value
qsr("eqIncome", weights = "rb050", data = eusilc)
# values by region
qsr("eqIncome", weights = "rb050",
breakdown = "db040", data = eusilc)
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