capm (version 0.9.1)

DesignSurvey: Survey design

Description

A wraper for svydesign function from the survey package, to define one of the following survey designs: two-stage cluster, simple (systematic) or stratified. In the first case, weights are calculated considering a probability proportional to size sampling with replacement for the first stage and a simple random sampling for the second stage. Finite population correction is specified as the population size for each level of sampling.

Usage

DesignSurvey(sample = NULL, psu.ssu = NULL, psu.col = NULL, ssu.col = NULL, psu.2cd = NULL, N = NULL, strata = NULL, ...)

Arguments

sample

data.frame with sample observations. for two-stage cluster designs, one of the columns must contain unique identifiers for PSU and another column must contain unique identifiers for Secondary Sampling Units (SSU).

psu.ssu

data.frame with all Primary Sampling Units (PSU). First column contains PSU unique identifiers. Second column contains numeric PSU sizes. It is only used for two-stage cluster designs.

psu.col

the column of sample containing the psu identifiers (for two-stage cluster designs). It is only used for two-stage cluster designs.

ssu.col

the column of sample containing the ssu identifiers (for two-stage cluster designs). It is only used for two-stage cluster designs.

psu.2cd

value indicating that the survey is a two-stage cluster design and the number of psu included (for psu included more than once, each must be counted).

N

for simple designs, a numeric value representing the total of sampling units in the population. for a stratified design, it is a column of sample indicating, for each observation, the total of sampling units in its respective strata. N is ignored in two-stage cluster designs.

strata

for stratified designs, a column of sample indicating the strata memebership of each observation.

...

further arguments passed to svydesign function.

Value

An object of class survey.design.

Details

For two-stage cluster designs, a PSU appearing in both psu.ssu and in sample must have the same identifier. SSU identifiers must be unique but can appear more than once if there is more than one observation per SSU. sample argument must have just the varibles to be estimated plus the variables required to define the design (two-stage cluster or stratified).

References

Lumley, T. (2011). Complex surveys: A guide to analysis using R (Vol. 565). Wiley.

http://oswaldosantos.github.io/capm

Examples

# Load data with PSU identifiers and sizes.
data(psu.ssu)

# Load data with sample data.
data(survey.data)

## Specify a two-stage cluster design that included 20 PSU.
DesignSurvey(sample = survey.data, psu.ssu = psu.ssu,
             psu.col = 2, ssu.col = 1, psu.2cd = 20)
                             
## Assuming that survey.sampling is a simple design.
DesignSurvey(sample = survey.data, N = 144600)

## Assuming that survey.sampling is a stratified design.
# Hypothetical strata
strat <- survey.data
strat$strat <- 'Urban'
strat$strat[round(runif(5, 1, nrow(strat)))] <- 'Rural'
strat$strat.size <- 144000
strat$strat.size[strat$strat == 'Rural'] <- 600
DesignSurvey(strat, N = 'strat.size', strata = 'strat')