variance: Variance and confidence intervals of indicators on social...

In laeken: Estimation of Indicators on Social Exclusion and Poverty

Variance and confidence intervals of indicators on social exclusion and poverty

Description

Compute variance and confidence interval estimates of indicators on social exclusion and poverty.

Usage

variance(
  inc,
  weights = NULL,
  years = NULL,
  breakdown = NULL,
  design = NULL,
  cluster = NULL,
  data = NULL,
  indicator,
  alpha = 0.05,
  na.rm = FALSE,
  type = "bootstrap",
  gender = NULL,
  method = NULL,
  ...
)

Arguments

inc	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.
weights	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.
years	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.
breakdown	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.
design	optional; 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.
cluster	optional; 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.
data	an optional data.frame.
indicator	an object inheriting from the class "indicator" that contains the point estimates of the indicator (see arpr, qsr, rmpg or gini).
alpha	a numeric value giving the significance level to be used for computing the confidence interval(s) (i.e., the confidence level is 1 - alpha), or NULL.
na.rm	a logical indicating whether missing values should be removed.
type	a character string specifying the type of variance estimation to be used. Currently, only "bootstrap" is implemented for variance estimation based on bootstrap resampling (see bootVar).
gender	either a numeric vector giving the gender, or (if data is not NULL) a character string, an integer or a logical vector specifying the corresponding column of data.
method	a character string specifying the method to be used (only for gpg). Possible values are "mean" for the mean, and "median" for the median. If weights are provided, the weighted mean or weighted median is estimated.
...	additional arguments to be passed to bootVar.

Details

This is a wrapper function for computing variance and confidence interval estimates of indicators on social exclusion and poverty.

Value

An object of the same class as indicator is returned. See arpr, qsr, rmpg or gini for details on the components.

Author(s)

Andreas Alfons

References

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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v054.i15")}

See Also

bootVar, arpr, qsr, rmpg, gini

Examples

data(eusilc)
a <- arpr("eqIncome", weights = "rb050", data = eusilc)

## naive bootstrap
variance("eqIncome", weights = "rb050", design = "db040",
    data = eusilc, indicator = a, R = 50,
    bootType = "naive", seed = 123)

## bootstrap with calibration
variance("eqIncome", weights = "rb050", design = "db040",
    data = eusilc, indicator = a, R = 50,
    X = calibVars(eusilc$db040), seed = 123)

laeken documentation built on May 29, 2024, 4:42 a.m.