R: Bootstrap variance and confidence intervals of indicators on...

bootVar {laeken} | R Documentation

## Bootstrap 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 based on bootstrap resampling.

### Usage

    bootVar(inc, weights = NULL, years = NULL, breakdown = NULL,
      design = NULL, cluster = NULL, data = NULL, indicator, R = 100,
      bootType = c("calibrate", "naive"), X, totals = NULL, ciType = c("perc",
      "norm", "basic"), alpha = 0.05, seed = NULL, na.rm = FALSE,
      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`. If supplied, this is used as `strata` argument in the call to `boot`.
`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`).
`R` | a numeric value giving the number of bootstrap replicates.
`bootType` | a character string specifying the type of bootstap to be performed. Possible values are `"calibrate"` (for calibration of the sample weights of the resampled observations in every iteration) and `"naive"` (for a naive bootstrap without calibration of the sample weights).
`X` | if `bootType` is `"calibrate"`, a matrix of calibration variables.
`totals` | numeric; if `bootType` is `"calibrate"`, this gives the population totals. If `years` is `NULL`, a vector should be supplied, otherwise a matrix in which each row contains the population totals of the respective year. If this is `NULL` (the default), the population totals are computed from the sample weights using the Horvitz-Thompson estimator.
`ciType` | a character string specifying the type of confidence interval(s) to be computed. Possible values are `"perc"`, `"norm"` and `"basic"` (see `boot.ci`).
`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`.
`seed` | optional; an integer value to be used as the seed of the random number generator, or an integer vector containing the state of the random number generator to be restored.
`na.rm` | a logical indicating whether missing values should be removed.
`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.
`...` | if `bootType` is `"calibrate"`, additional arguments to be passed to `calibWeights`.

### Value

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

### Note

This function gives reasonable variance estimates for basic sample designs such as simple random sampling or stratified simple random sampling.

### 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. URL http://www.jstatsoft.org/v54/i15/

### See Also

`variance`, `calibWeights`, `arpr`, `qsr`, `rmpg`, `gini`

### Examples

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

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

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

[Package laeken version 0.4.6 Index]