Variance and confidence intervals of indicators on social exclusion and poverty
Compute variance and confidence interval estimates of indicators on social exclusion and poverty.
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, ...)
inc |
either a numeric vector giving the equivalized disposable income,
or (if |
weights |
optional; either a numeric vector giving the personal sample
weights, or (if |
years |
optional; either a numeric vector giving the different years of
the survey, or (if |
breakdown |
optional; either a numeric vector giving different domains,
or (if |
design |
optional; either an integer vector or factor giving different
strata for stratified sampling designs, or (if |
cluster |
optional; either an integer vector or factor giving different
clusters for cluster sampling designs, or (if |
data |
an optional |
indicator |
an object inheriting from the class |
alpha |
a numeric value giving the significance level to be used for
computing the confidence interval(s) (i.e., the confidence level is 1 -
|
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 |
gender |
either a numeric vector giving the gender, or (if |
method |
a character string specifying the method to be used (only for
|
... |
additional arguments to be passed to |
This is a wrapper function for computing variance and confidence interval estimates of indicators on social exclusion and poverty.
Andreas Alfons
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. URL http://www.jstatsoft.org/v54/i15/
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)
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